From 7caa61230528a9b91a32c9a1a6efd51f05afac73 Mon Sep 17 00:00:00 2001 From: Sepand Haghighi Date: Tue, 15 Oct 2024 21:22:15 +0330 Subject: [PATCH] Version 4.1 (#563) * rel : migrate to version 4.1 * rel : CHANGELOG.md updated for version 4.1 * rel : document updated for version 4.1 * doc : minor edit in feature_request.yml * doc : minor edit in Document.ipynb installation section * doc : DigitalOcean logo added to README.md --- .github/ISSUE_TEMPLATE/bug_report.yml | 1 + .github/ISSUE_TEMPLATE/feature_request.yml | 2 +- CHANGELOG.md | 4 +- Document/Document.ipynb | 132 ++++++++++---------- Document/Document_files/cm1.html | 5 +- Document/Document_files/cm1.obj | 2 +- Document/Document_files/cm1_colored.html | 5 +- Document/Document_files/cm1_colored2.html | 5 +- Document/Document_files/cm1_filtered.html | 5 +- Document/Document_files/cm1_filtered2.html | 5 +- Document/Document_files/cm1_no_vectors.obj | 2 +- Document/Document_files/cm1_normalized.html | 5 +- Document/Document_files/cm1_stat.obj | 2 +- Document/Document_files/cm1_summary.html | 5 +- Document/Example1.ipynb | 10 +- Document/Example1_files/cm1.html | 5 +- Document/Example1_files/cm2.html | 5 +- Document/Example1_files/cm3.html | 5 +- Document/Example2.ipynb | 10 +- Document/Example4.ipynb | 6 +- Document/Example4_files/cm.obj | 2 +- Document/Example4_files/cm_no_vectors.obj | 2 +- Document/Example4_files/cm_stat.obj | 2 +- Document/Example6.ipynb | 98 +++++++-------- Document/Example7.ipynb | 17 ++- Document/Example8.ipynb | 10 +- Otherfiles/meta.yaml | 2 +- Otherfiles/test.html | 5 +- Otherfiles/test.obj | 2 +- Otherfiles/version_check.py | 2 +- README.md | 11 +- SECURITY.md | 4 +- pycm/params.py | 2 +- setup.py | 4 +- 34 files changed, 211 insertions(+), 173 deletions(-) diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml index b1d8b209..6c6c91ad 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.yml +++ b/.github/ISSUE_TEMPLATE/bug_report.yml @@ -86,6 +86,7 @@ body: label: PyCM version description: Which version of PyCM are you using? options: + - PyCM 4.1 - PyCM 4.0 - PyCM 3.9 - PyCM 3.8 diff --git a/.github/ISSUE_TEMPLATE/feature_request.yml b/.github/ISSUE_TEMPLATE/feature_request.yml index 305d2f85..139114ca 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.yml +++ b/.github/ISSUE_TEMPLATE/feature_request.yml @@ -27,7 +27,7 @@ body: validations: required: false - type: textarea - id: aditional-context + id: additional-context attributes: label: Additional context placeholder: > diff --git a/CHANGELOG.md b/CHANGELOG.md index 7f0918ef..5d58288b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html). ## [Unreleased] +## [4.1] - 2024-10-17 ### Added - 5 new distance/similarity 1. KoppenI @@ -749,7 +750,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0. - TPR - documents and `README.md` -[Unreleased]: https://github.com/sepandhaghighi/pycm/compare/v4.0...dev +[Unreleased]: https://github.com/sepandhaghighi/pycm/compare/v4.1...dev +[4.1]: https://github.com/sepandhaghighi/pycm/compare/v4.0...v4.1 [4.0]: https://github.com/sepandhaghighi/pycm/compare/v3.9...v4.0 [3.9]: https://github.com/sepandhaghighi/pycm/compare/v3.8...v3.9 [3.8]: https://github.com/sepandhaghighi/pycm/compare/v3.7...v3.8 diff --git a/Document/Document.ipynb b/Document/Document.ipynb index f01f2b0f..f50aaaf9 100644 --- a/Document/Document.ipynb +++ b/Document/Document.ipynb @@ -18,7 +18,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Version : 4.0 " + "### Version : 4.1 " ] }, { @@ -321,7 +321,7 @@ "\n", "\n", "- Check [Python Packaging User Guide](https://packaging.python.org/installing/) \n", - "- Run `pip install pycm==4.0` (Need root access)" + "- Run `pip install pycm==4.1`" ] }, { @@ -329,8 +329,8 @@ "metadata": {}, "source": [ "### Source code\n", - "- Download [Version 4.0](https://github.com/sepandhaghighi/pycm/archive/v4.0.zip) or [Latest Source](https://github.com/sepandhaghighi/pycm/archive/dev.zip)\n", - "- Run `pip install .` (Need root access)" + "- Download [Version 4.1](https://github.com/sepandhaghighi/pycm/archive/v4.1.zip) or [Latest Source](https://github.com/sepandhaghighi/pycm/archive/dev.zip)\n", + "- Run `pip install .`" ] }, { @@ -340,7 +340,7 @@ "### Conda\n", "\n", "- Check [Conda Managing Package](https://conda.io/docs/user-guide/tasks/manage-pkgs.html#installing-packages-from-anaconda-org)\n", - "- `conda install -c sepandhaghighi pycm` (Need root access)" + "- `conda install -c sepandhaghighi pycm`" ] }, { @@ -358,7 +358,7 @@ "- Download and install [Python3.x](https://www.python.org/downloads/) (>=3.6, 64/32 bit) \n", "\t- Select `Add to PATH` option\n", "\t- Select `Install pip` option\n", - "- Run `pip install pycm` or `pip3 install pycm` (Need root access)\n", + "- Run `pip install pycm` or `pip3 install pycm`\n", "- Configure Python interpreter\n", "```\n", ">> pyversion PYTHON_EXECUTABLE_FULL_PATH\n", @@ -960,7 +960,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.0-py3.5.egg\\pycm\\pycm_util.py:400: RuntimeWarning: Used classes is not a subset of classes in actual and predict vectors.\n" + "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.1-py3.5.egg\\pycm\\utils.py:399: RuntimeWarning: Specified classes are not a subset of the classes in the actual and predicted vectors.\n" ] } ], @@ -1613,9 +1613,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "L2 {'L2': 6, 'L3': 1, 'L1': 4}\n", - "L3 {'L2': 2, 'L3': 3, 'L1': 1}\n", - "L1 {'L2': 2, 'L3': 3, 'L1': 1}\n" + "L3 {'L3': 3, 'L2': 2, 'L1': 1}\n", + "L2 {'L3': 1, 'L2': 6, 'L1': 4}\n", + "L1 {'L3': 3, 'L2': 2, 'L1': 1}\n" ] } ], @@ -1632,7 +1632,7 @@ { "data": { "text/plain": [ - "('L2', {'L1': 4, 'L2': 6, 'L3': 1})" + "('L3', {'L1': 1, 'L2': 2, 'L3': 3})" ] }, "execution_count": 51, @@ -1676,8 +1676,8 @@ { "data": { "text/plain": [ - "[('L2', {'L1': 4, 'L2': 6, 'L3': 1}),\n", - " ('L3', {'L1': 1, 'L2': 2, 'L3': 3}),\n", + "[('L3', {'L1': 1, 'L2': 2, 'L3': 3}),\n", + " ('L2', {'L1': 4, 'L2': 6, 'L3': 1}),\n", " ('L1', {'L1': 1, 'L2': 2, 'L3': 3})]" ] }, @@ -2378,7 +2378,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -2396,7 +2396,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 67, @@ -2428,7 +2428,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 68, @@ -2460,7 +2460,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 69, @@ -2492,7 +2492,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 70, @@ -2524,7 +2524,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 71, @@ -3193,7 +3193,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 92, @@ -3250,7 +3250,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.0-py3.5.egg\\pycm\\pycm_curve.py:382: RuntimeWarning: The curve axes contain non-numerical value(s).\n" + "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.1-py3.5.egg\\pycm\\curve.py:382: RuntimeWarning: The curve contains non-numerical value(s).\n" ] }, { @@ -3284,7 +3284,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 94, @@ -8110,7 +8110,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.0-py3.5.egg\\pycm\\pycm_obj.py:850: RuntimeWarning: The weight format is wrong, the result is for unweighted kappa.\n" + "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.1-py3.5.egg\\pycm\\cm.py:850: RuntimeWarning: Invalid weight format; the result is for unweighted kappa.\n" ] }, { @@ -12200,7 +12200,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.0-py3.5.egg\\pycm\\pycm_obj.py:873: RuntimeWarning: The weight format is wrong, the result is for unweighted alpha.\n" + "C:\\Users\\Sepkjaer\\AppData\\Local\\Programs\\Python\\Python35-32\\lib\\site-packages\\pycm-4.1-py3.5.egg\\pycm\\cm.py:873: RuntimeWarning: Invalid weight format; the result is for unweighted alpha.\n" ] }, { @@ -14630,7 +14630,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The type of input vectors is assumed to be a list or a NumPy array\n" + "Input vectors must be provided as a list or a NumPy array.\n" ] } ], @@ -14652,7 +14652,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors must have same length\n" + "Input vectors must have the same length.\n" ] } ], @@ -14672,7 +14672,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors are empty\n" + "Input vectors must not be empty.\n" ] } ], @@ -14692,7 +14692,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors must have same length\n" + "Input vectors must have the same length.\n" ] } ], @@ -14712,7 +14712,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input confusion matrix format error\n" + "Invalid input confusion matrix format.\n" ] } ], @@ -14732,7 +14732,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Type of the input matrix classes is assumed be the same\n" + "All input matrix classes must be of the same type.\n" ] } ], @@ -14752,7 +14752,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Number of the classes is lower than 2\n" + "The number of classes must be at least 2.\n" ] } ], @@ -14772,7 +14772,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The input type is supposed to be dictionary but it's not!\n" + "Input must be provided as a dictionary.\n" ] } ], @@ -14792,7 +14792,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The domain of all ConfusionMatrix objects must be same! The sample size or the number of classes are different.\n" + "All ConfusionMatrix objects must have the same domain (same sample size and number of classes).\n" ] } ], @@ -14812,7 +14812,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The input is supposed to consist of pycm.ConfusionMatrix object but it's not!\n" + "Input must be a dictionary containing pycm.ConfusionMatrix objects.\n" ] } ], @@ -14832,7 +14832,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Lower than two confusion matrices is given for comparing. The minimum number of confusion matrix for comparing is 2.\n" + "At least 2 confusion matrices are required for comparison.\n" ] } ], @@ -14852,7 +14852,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The class_weight type must be dictionary and also must be specified for all of the classes.\n" + "`class_weight` must be a dictionary and specified for all classes.\n" ] } ], @@ -14875,7 +14875,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The class_benchmark_weight type must be dictionary and also must be specified for all of the class benchmarks.\n" + "`class_benchmark_weight` must be a dictionary and specified for all class benchmarks.\n" ] } ], @@ -14897,7 +14897,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The overall_benchmark_weight type must be dictionary and also must be specified for all of the overall benchmarks.\n" + "`overall_benchmark_weight` must be a dictionary and specified for all overall benchmarks.\n" ] } ], @@ -14919,8 +14919,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CI calculation for this parameter is not supported on this version of pycm.\n", - "Supported parameters : TPR,TNR,PPV,NPV,ACC,PLR,NLR,FPR,FNR,AUC,PRE,Kappa,Overall ACC\n" + "Confidence interval calculation for this parameter is not supported in this version of pycm.\n", + " Supported parameters are: TPR, TNR, PPV, NPV, ACC, PLR, NLR, FPR, FNR, AUC, PRE, Kappa, Overall ACC\n" ] } ], @@ -14940,7 +14940,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The input type is supposed to be string but it's not!\n" + "Input must be provided as a string.\n" ] } ], @@ -15000,7 +15000,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The weight type must be dictionary and also must be specified for all of the classes.\n" + "`weight` must be a dictionary and specified for all classes.\n" ] } ], @@ -15020,7 +15020,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "This option only works in vector mode\n" + "This option is only available in vector mode.\n" ] } ], @@ -15040,7 +15040,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The input type is supposed to be pycm.ConfusionMatrix object but it's not!\n" + "Input must be an instance of pycm.ConfusionMatrix.\n" ] } ], @@ -15060,7 +15060,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Number of the classes is lower than 2\n" + "The number of classes must be at least 2.\n" ] } ], @@ -15080,7 +15080,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The classes list isn't unique. It contains duplicated labels.\n" + "`classes` must contain unique labels with no duplicates.\n" ] } ], @@ -15100,7 +15100,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The type of input vectors is assumed to be a list or a NumPy array\n" + "Input vectors must be provided as a list or a NumPy array.\n" ] } ], @@ -15120,7 +15120,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors must have same length\n" + "Input vectors must have the same length.\n" ] } ], @@ -15140,7 +15140,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The sum of probability values must be one\n" + "The sum of the probability values must equal 1.\n" ] } ], @@ -15163,7 +15163,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The type of classes is assumed to be list\n" + "`classes` must be provided as a list.\n" ] } ], @@ -15186,7 +15186,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The classes don't match to actual_vector\n" + "`classes` does not match the actual vector.\n" ] } ], @@ -15209,7 +15209,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Number of the classes is lower than 2\n" + "The number of classes must be at least 2.\n" ] } ], @@ -15232,7 +15232,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The elements of the probability vector can only contain numeric values\n" + "Probability vector elements must be numeric.\n" ] } ], @@ -15255,7 +15255,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The type of thresholds is assumed to be list or NumPy array\n" + "`thresholds` must be provided as a list or a NumPy array.\n" ] } ], @@ -15279,7 +15279,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Number of the thresholds is lower than 2\n" + "The number of thresholds must be at least 2.\n" ] } ], @@ -15303,7 +15303,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The thresholds can only contain numeric values\n" + "`thresholds` must contain only numeric values.\n" ] } ], @@ -15327,7 +15327,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The classes list isn't unique. It contains duplicated labels.\n" + "`classes` must contain unique labels with no duplicates.\n" ] } ], @@ -15350,7 +15350,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Probability vector elements must have same length and equal to classes\n" + "All elements of the probability vector must have the same length and match the number of classes.\n" ] } ], @@ -15373,7 +15373,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The numeric integral method can only be selected between 'trapezoidal' and 'midpoint'!\n" + "The integral method must be either 'trapezoidal' or 'midpoint'.\n" ] } ], @@ -15397,7 +15397,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Class extraction from input failed. Input vectors should be a list of sets with unified types.\n" + "Failed to extract classes from input. Input vectors should be a list of sets with unified types.\n" ] } ], @@ -15417,7 +15417,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Given class name is not among problem's classes.\n" + "The specified class name is not among the confusion matrix's classes.\n" ] } ], @@ -15438,7 +15438,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Given index is out of vector's range.\n" + "Index is out of range for the given vector.\n" ] } ], @@ -15458,7 +15458,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The type of input vectors is assumed to be a list or a NumPy array\n" + "Input vectors must be provided as a list or a NumPy array.\n" ] } ], @@ -15478,7 +15478,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors must have same length\n" + "Input vectors must have the same length.\n" ] } ], @@ -15498,7 +15498,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Input vectors are empty\n" + "Input vectors must not be empty.\n" ] } ], @@ -15518,7 +15518,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The classes list isn't unique. It contains duplicated labels.\n" + "`classes` must contain unique labels with no duplicates.\n" ] } ], diff --git a/Document/Document_files/cm1.html b/Document/Document_files/cm1.html index 29c91105..d20d36a6 100644 --- a/Document/Document_files/cm1.html +++ b/Document/Document_files/cm1.html @@ -21,8 +21,7 @@

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    +

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    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

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b/Document/Document_files/cm1_summary.html @@ -21,8 +21,7 @@

    Dataset Type :

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    • Note 1 : Recommended statistics for this type of classification highlighted in aqua

    -

    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

    +

    Note 2 : The recommendation system assumes the input is the result of classification over the entire dataset, not just a subset. If the confusion matrix is based on test data classification, the recommendation may not be valid.

    Confusion Matrix (Normalized):

    @@ -222,6 +221,6 @@

    Class Statistics :

    Test outcome negative
    -

    Generated By PyCM Version 4.0

    +

    Generated By PyCM Version 4.1

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    Dataset Type :

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    -

    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

    +

    Note 2 : The recommendation system assumes the input is the result of classification over the entire dataset, not just a subset. If the confusion matrix is based on test data classification, the recommendation may not be valid.

    Confusion Matrix :

    @@ -787,6 +786,6 @@

    Class Statistics :

    Similarity index
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    Generated By PyCM Version 4.0

    +

    Generated By PyCM Version 4.1

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    Dataset Type :

  • Balanced

    • Note 1 : Recommended statistics for this type of classification highlighted in aqua

    -

    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

    +

    Note 2 : The recommendation system assumes the input is the result of classification over the entire dataset, not just a subset. If the confusion matrix is based on test data classification, the recommendation may not be valid.

    Confusion Matrix :

    @@ -787,6 +786,6 @@

    Class Statistics :

    Similarity index
    -

    Generated By PyCM Version 4.0

    +

    Generated By PyCM Version 4.1

    diff --git a/Document/Example1_files/cm3.html b/Document/Example1_files/cm3.html index 69e93cd1..7c234b27 100644 --- a/Document/Example1_files/cm3.html +++ b/Document/Example1_files/cm3.html @@ -21,8 +21,7 @@

    Dataset Type :

  • Balanced

    • Note 1 : Recommended statistics for this type of classification highlighted in aqua

    -

    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

    +

    Note 2 : The recommendation system assumes the input is the result of classification over the entire dataset, not just a subset. If the confusion matrix is based on test data classification, the recommendation may not be valid.

    Confusion Matrix :

    @@ -787,6 +786,6 @@

    Class Statistics :

    Similarity index
    -

    Generated By PyCM Version 4.0

    +

    Generated By PyCM Version 4.1

    diff --git a/Document/Example2.ipynb b/Document/Example2.ipynb index 79f61032..bc13e0ba 100644 --- a/Document/Example2.ipynb +++ b/Document/Example2.ipynb @@ -62,7 +62,15 @@ "metadata": { "hide_output": true }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Keyring is skipped due to an exception: invalid syntax (core.py, line 48)\n" + ] + } + ], "source": [ "!{sys.executable} -m pip -q -q install matplotlib;" ] diff --git a/Document/Example4.ipynb b/Document/Example4.ipynb index cee37f6b..b3dcee9e 100644 --- a/Document/Example4.ipynb +++ b/Document/Example4.ipynb @@ -569,7 +569,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{\"Predict-Vector\": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], \"Sample-Weight\": null, \"Digit\": 5, \"Actual-Vector\": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200], \"Transpose\": false, \"Prob-Vector\": null, \"Imbalanced\": true, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]]}\n" + "{\"Digit\": 5, \"Sample-Weight\": null, \"Imbalanced\": true, \"Prob-Vector\": null, \"Predict-Vector\": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], \"Transpose\": false, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]], \"Actual-Vector\": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200]}\n" ] } ], @@ -586,7 +586,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{\"Class-Stat\": {\"TN\": {\"200\": 3, \"100\": 9, \"500\": 16, \"600\": 19}, \"PRE\": {\"200\": 0.8, \"500\": 0.15, \"100\": 0.0, \"600\": 0.05}, \"N\": {\"200\": 4, \"500\": 17, \"100\": 20, \"600\": 19}, \"BB\": {\"200\": 0.375, \"500\": 0.3333333333333333, \"100\": 0.0, \"600\": 0.0}, \"F1\": {\"200\": 0.5217391304347826, \"500\": 0.4, \"100\": 0.0, \"600\": 0.0}, \"FDR\": {\"200\": 0.1428571428571429, \"500\": 0.5, \"100\": 1.0, \"600\": \"None\"}, \"TP\": {\"200\": 6, \"100\": 0, \"500\": 1, \"600\": 0}, \"ACC\": {\"200\": 0.45, \"500\": 0.85, \"100\": 0.45, \"600\": 0.95}, \"IS\": {\"200\": 0.09953567355091428, \"500\": 1.736965594166206, \"100\": \"None\", \"600\": \"None\"}, \"TNR\": {\"200\": 0.75, \"500\": 0.9411764705882353, \"100\": 0.45, \"600\": 1.0}, \"TON\": {\"200\": 13, \"500\": 18, \"100\": 9, \"600\": 20}, \"PLR\": {\"200\": 1.5, \"500\": 5.666666666666665, \"100\": \"None\", \"600\": \"None\"}, \"J\": {\"200\": 0.35294117647058826, \"500\": 0.25, \"100\": 0.0, \"600\": 0.0}, \"RACCU\": {\"200\": 0.33062499999999995, \"500\": 0.015625, \"100\": 0.07562500000000001, \"600\": 0.0006250000000000001}, \"F0.5\": {\"200\": 0.6818181818181818, \"500\": 0.45454545454545453, \"100\": 0.0, \"600\": 0.0}, \"dInd\": {\"200\": 0.673145600891813, \"500\": 0.6692567908186672, \"100\": \"None\", \"600\": 1.0}, \"GI\": {\"200\": 0.125, \"500\": 0.27450980392156854, \"100\": \"None\", \"600\": 0.0}, \"FNR\": {\"200\": 0.625, \"500\": 0.6666666666666667, \"100\": \"None\", \"600\": 1.0}, \"F2\": {\"200\": 0.4225352112676056, \"500\": 0.35714285714285715, \"100\": 0.0, \"600\": 0.0}, \"MK\": {\"200\": 0.08791208791208782, \"500\": 0.38888888888888884, \"100\": 0.0, \"600\": \"None\"}, \"HD\": {\"200\": 11, \"500\": 3, \"100\": 11, \"600\": 1}, \"AUPR\": {\"200\": 0.6160714285714286, \"500\": 0.41666666666666663, \"100\": \"None\", \"600\": \"None\"}, \"RACC\": {\"200\": 0.28, \"500\": 0.015, \"100\": 0.0, \"600\": 0.0}, \"P\": {\"200\": 16, \"500\": 3, \"100\": 0, \"600\": 1}, \"AUCI\": {\"200\": \"Poor\", \"500\": \"Fair\", \"100\": \"None\", \"600\": \"Poor\"}, \"FPR\": {\"200\": 0.25, \"500\": 0.05882352941176472, \"100\": 0.55, \"600\": 0.0}, \"Y\": {\"200\": 0.125, \"500\": 0.27450980392156854, \"100\": \"None\", \"600\": 0.0}, \"FOR\": {\"200\": 0.7692307692307692, \"500\": 0.11111111111111116, \"100\": 0.0, \"600\": 0.050000000000000044}, \"TPR\": {\"200\": 0.375, \"500\": 0.3333333333333333, \"100\": \"None\", \"600\": 0.0}, \"FN\": {\"200\": 10, \"100\": 0, \"500\": 2, \"600\": 1}, \"G\": {\"200\": 0.5669467095138409, \"500\": 0.408248290463863, \"100\": \"None\", \"600\": \"None\"}, \"POP\": {\"200\": 20, \"500\": 20, \"100\": 20, \"600\": 20}, \"MCEN\": {\"200\": 0.3739448088748241, \"500\": 0.5802792108518123, \"100\": 0.3349590631259315, \"600\": 0.0}, \"PLRI\": {\"200\": \"Poor\", \"500\": \"Fair\", \"100\": \"None\", \"600\": \"None\"}, \"DOR\": {\"200\": 1.7999999999999998, \"500\": 7.999999999999997, \"100\": \"None\", \"600\": \"None\"}, \"AGM\": {\"200\": 0.5669417382415922, \"500\": 0.7351956938438939, \"100\": \"None\", \"600\": 0}, \"GM\": {\"200\": 0.5303300858899106, \"500\": 0.5601120336112039, \"100\": \"None\", \"600\": 0.0}, \"TOP\": {\"200\": 7, \"500\": 2, \"100\": 11, \"600\": 0}, \"sInd\": {\"200\": 0.5240141808835057, \"500\": 0.5267639848569737, \"100\": \"None\", \"600\": 0.29289321881345254}, \"DP\": {\"200\": 0.1407391082701595, \"500\": 0.49789960499474867, \"100\": \"None\", \"600\": \"None\"}, \"ERR\": {\"200\": 0.55, \"500\": 0.15000000000000002, \"100\": 0.55, \"600\": 0.050000000000000044}, \"NLR\": {\"200\": 0.8333333333333334, \"500\": 0.7083333333333334, \"100\": \"None\", \"600\": 1.0}, \"NPV\": {\"200\": 0.23076923076923078, \"500\": 0.8888888888888888, \"100\": 1.0, \"600\": 0.95}, \"Q\": {\"200\": 0.28571428571428575, \"500\": 0.7777777777777778, \"100\": \"None\", \"600\": \"None\"}, \"ICSI\": {\"200\": 0.2321428571428572, \"500\": -0.16666666666666674, \"100\": \"None\", \"600\": \"None\"}, \"LS\": {\"200\": 1.0714285714285714, \"500\": 3.3333333333333335, \"100\": \"None\", \"600\": \"None\"}, \"OP\": {\"200\": 0.1166666666666667, \"500\": 0.373076923076923, \"100\": \"None\", \"600\": -0.050000000000000044}, \"CEN\": {\"200\": 0.3570795472009597, \"500\": 0.5389466410223563, \"100\": 0.3349590631259315, \"600\": 0.0}, \"AUC\": {\"200\": 0.5625, \"500\": 0.6372549019607843, \"100\": \"None\", \"600\": 0.5}, \"NLRI\": {\"200\": \"Negligible\", \"500\": \"Negligible\", \"100\": \"None\", \"600\": \"Negligible\"}, \"IBA\": {\"200\": 0.17578125, \"500\": 0.1230296039984621, \"100\": \"None\", \"600\": 0.0}, \"MCCI\": {\"200\": \"Negligible\", \"500\": \"Weak\", \"100\": \"None\", \"600\": \"None\"}, \"DPI\": {\"200\": \"Poor\", \"500\": \"Poor\", \"100\": \"None\", \"600\": \"None\"}, \"OC\": {\"200\": 0.8571428571428571, \"500\": 0.5, \"100\": \"None\", \"600\": \"None\"}, \"FP\": {\"200\": 1, \"100\": 11, \"500\": 1, \"600\": 0}, \"QI\": {\"200\": \"Weak\", \"500\": \"Strong\", \"100\": \"None\", \"600\": \"None\"}, \"OOC\": {\"200\": 0.5669467095138409, \"500\": 0.4082482904638631, \"100\": \"None\", \"600\": \"None\"}, \"BCD\": {\"200\": 0.225, \"500\": 0.025, \"100\": 0.275, \"600\": 0.025}, \"AGF\": {\"200\": 0.33642097801219245, \"500\": 0.5665926996700735, \"100\": 0.0, \"600\": 0.0}, \"AM\": {\"200\": -9, \"500\": -1, \"100\": 11, \"600\": -1}, \"BM\": {\"200\": 0.125, \"500\": 0.27450980392156854, \"100\": \"None\", \"600\": 0.0}, \"MCC\": {\"200\": 0.10482848367219183, \"500\": 0.32673201960653564, \"100\": \"None\", \"600\": \"None\"}, \"PPV\": {\"200\": 0.8571428571428571, \"500\": 0.5, \"100\": 0.0, \"600\": \"None\"}}, \"Predict-Vector\": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], \"Sample-Weight\": null, \"Digit\": 5, \"Actual-Vector\": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200], \"Transpose\": false, \"Prob-Vector\": null, \"Overall-Stat\": {\"FNR Macro\": \"None\", \"SOA5(Cramer)\": \"None\", \"Reference Entropy\": 0.8841837197791889, \"Cramer V\": \"None\", \"Bennett S\": 0.1333333333333333, \"Overall MCC\": 0.1264200803632855, \"Kappa 95% CI\": [-0.21849807698648957, 0.3745264457808156], \"Chi-Squared\": \"None\", \"Overall CEN\": 0.3648028121279775, \"Hamming Loss\": 0.65, \"TNR Macro\": 0.7852941176470588, \"Overall J\": [0.6029411764705883, 0.15073529411764708], \"Pearson C\": \"None\", \"Overall RACC\": 0.29500000000000004, \"NPV Macro\": 0.7674145299145299, \"Lambda A\": 0.0, \"Conditional Entropy\": 1.235789374242786, \"Mutual Information\": 0.10087710767390168, \"SOA1(Landis & Koch)\": \"Slight\", \"SOA10(Pearson C)\": \"None\", \"SOA2(Fleiss)\": \"Poor\", \"Joint Entropy\": 2.119973094021975, \"FNR Micro\": 0.65, \"Bangdiwala B\": 0.3135593220338983, \"Kappa\": 0.07801418439716304, \"Kappa Unbiased\": -0.12554112554112543, \"KL Divergence\": \"None\", \"Phi-Squared\": \"None\", \"SOA6(Matthews)\": \"Negligible\", \"AUNP\": \"None\", \"TPR Micro\": 0.35, \"RR\": 5.0, \"Overall ACC\": 0.35, \"Gwet AC1\": 0.19504643962848295, \"FPR Micro\": 0.21666666666666667, \"AUNU\": \"None\", \"SOA9(Krippendorff Alpha)\": \"Low\", \"SOA4(Cicchetti)\": \"Poor\", \"SOA8(Lambda B)\": \"None\", \"ARI\": 0.02298247455136956, \"NPV Micro\": 0.7833333333333333, \"FPR Macro\": 0.2147058823529412, \"ACC Macro\": 0.675, \"TPR Macro\": \"None\", \"PPV Micro\": 0.35, \"Standard Error\": 0.1066536450385077, \"RCI\": 0.11409066398451011, \"Lambda B\": 0.0, \"NIR\": 0.8, \"Zero-one Loss\": 13, \"CSI\": \"None\", \"Kappa Standard Error\": 0.15128176601206766, \"Cross Entropy\": 1.709947752496911, \"TNR Micro\": 0.7833333333333333, \"F1 Macro\": 0.23043478260869565, \"SOA7(Lambda A)\": \"None\", \"PPV Macro\": \"None\", \"P-Value\": 0.9999981549942787, \"95% CI\": [0.14095885572452488, 0.559041144275475], \"F1 Micro\": 0.35, \"Scott PI\": -0.12554112554112543, \"Response Entropy\": 1.3366664819166876, \"Chi-Squared DF\": 9, \"Overall RACCU\": 0.42249999999999993, \"Kappa No Prevalence\": -0.30000000000000004, \"Overall MCEN\": 0.3746281299595305, \"CBA\": 0.17708333333333331, \"Krippendorff Alpha\": -0.09740259740259723, \"SOA3(Altman)\": \"Poor\"}, \"Imbalanced\": true, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]]}\n" + "{\"Overall-Stat\": {\"TNR Macro\": 0.7852941176470588, \"Kappa Standard Error\": 0.15128176601206766, \"Overall MCEN\": 0.3746281299595305, \"CBA\": 0.17708333333333331, \"F1 Micro\": 0.35, \"TPR Macro\": \"None\", \"Kappa 95% CI\": [-0.21849807698648957, 0.3745264457808156], \"SOA1(Landis & Koch)\": \"Slight\", \"ACC Macro\": 0.675, \"NPV Micro\": 0.7833333333333333, \"Hamming Loss\": 0.65, \"AUNP\": \"None\", \"Standard Error\": 0.1066536450385077, \"PPV Micro\": 0.35, \"TPR Micro\": 0.35, \"Overall MCC\": 0.1264200803632855, \"Cramer V\": 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\"Lambda A\": 0.0, \"SOA6(Matthews)\": \"Negligible\", \"SOA10(Pearson C)\": \"None\", \"Cross Entropy\": 1.709947752496911, \"Phi-Squared\": \"None\", \"95% CI\": [0.14095885572452488, 0.559041144275475], \"CSI\": \"None\", \"SOA4(Cicchetti)\": \"Poor\", \"FPR Macro\": 0.2147058823529412, \"FPR Micro\": 0.21666666666666667, \"Overall CEN\": 0.3648028121279775, \"Reference Entropy\": 0.8841837197791889, \"SOA9(Krippendorff Alpha)\": \"Low\", \"NPV Macro\": 0.7674145299145299, \"Kappa No Prevalence\": -0.30000000000000004, \"TNR Micro\": 0.7833333333333333, \"F1 Macro\": 0.23043478260869565, \"Mutual Information\": 0.10087710767390168, \"FNR Macro\": \"None\", \"Overall RACC\": 0.29500000000000004}, \"Digit\": 5, \"Sample-Weight\": null, \"Class-Stat\": {\"IS\": {\"200\": 0.09953567355091428, \"500\": 1.736965594166206, \"100\": \"None\", \"600\": \"None\"}, \"PLRI\": {\"200\": \"Poor\", \"500\": \"Fair\", \"100\": \"None\", \"600\": \"None\"}, \"MCCI\": {\"200\": \"Negligible\", 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\"None\", \"600\": 1.0}, \"AUC\": {\"200\": 0.5625, \"500\": 0.6372549019607843, \"100\": \"None\", \"600\": 0.5}, \"OC\": {\"200\": 0.8571428571428571, \"500\": 0.5, \"100\": \"None\", \"600\": \"None\"}, \"TNR\": {\"200\": 0.75, \"500\": 0.9411764705882353, \"100\": 0.45, \"600\": 1.0}, \"TPR\": {\"200\": 0.375, \"500\": 0.3333333333333333, \"100\": \"None\", \"600\": 0.0}, \"FNR\": {\"200\": 0.625, \"500\": 0.6666666666666667, \"100\": \"None\", \"600\": 1.0}, \"MCEN\": {\"200\": 0.3739448088748241, \"500\": 0.5802792108518123, \"100\": 0.3349590631259315, \"600\": 0.0}, \"F1\": {\"200\": 0.5217391304347826, \"500\": 0.4, \"100\": 0.0, \"600\": 0.0}, \"ERR\": {\"200\": 0.55, \"500\": 0.15000000000000002, \"100\": 0.55, \"600\": 0.050000000000000044}, \"MCC\": {\"200\": 0.10482848367219183, \"500\": 0.32673201960653564, \"100\": \"None\", \"600\": \"None\"}, \"GI\": {\"200\": 0.125, \"500\": 0.27450980392156854, \"100\": \"None\", \"600\": 0.0}, \"NLRI\": {\"200\": \"Negligible\", \"500\": \"Negligible\", \"100\": \"None\", \"600\": \"Negligible\"}, \"POP\": {\"200\": 20, \"500\": 20, \"100\": 20, \"600\": 20}, \"N\": {\"200\": 4, \"500\": 17, \"100\": 20, \"600\": 19}, \"MK\": {\"200\": 0.08791208791208782, \"500\": 0.38888888888888884, \"100\": 0.0, \"600\": \"None\"}, \"AGF\": {\"200\": 0.33642097801219245, \"500\": 0.5665926996700735, \"100\": 0.0, \"600\": 0.0}, \"DP\": {\"200\": 0.1407391082701595, \"500\": 0.49789960499474867, \"100\": \"None\", \"600\": \"None\"}, \"NPV\": {\"200\": 0.23076923076923078, \"500\": 0.8888888888888888, \"100\": 1.0, \"600\": 0.95}, \"AUPR\": {\"200\": 0.6160714285714286, \"500\": 0.41666666666666663, \"100\": \"None\", \"600\": \"None\"}, \"FDR\": {\"200\": 0.1428571428571429, \"500\": 0.5, \"100\": 1.0, \"600\": \"None\"}, \"TP\": {\"200\": 6, \"100\": 0, \"500\": 1, \"600\": 0}, \"HD\": {\"200\": 11, \"500\": 3, \"100\": 11, \"600\": 1}, \"DOR\": {\"200\": 1.7999999999999998, \"500\": 7.999999999999997, \"100\": \"None\", \"600\": \"None\"}, \"AUCI\": {\"200\": \"Poor\", \"500\": \"Fair\", \"100\": \"None\", \"600\": \"Poor\"}, \"CEN\": {\"200\": 0.3570795472009597, \"500\": 0.5389466410223563, \"100\": 0.3349590631259315, \"600\": 0.0}, \"PRE\": {\"200\": 0.8, \"500\": 0.15, \"100\": 0.0, \"600\": 0.05}, \"FP\": {\"200\": 1, \"100\": 11, \"500\": 1, \"600\": 0}, \"QI\": {\"200\": \"Weak\", \"500\": \"Strong\", \"100\": \"None\", \"600\": \"None\"}, \"ICSI\": {\"200\": 0.2321428571428572, \"500\": -0.16666666666666674, \"100\": \"None\", \"600\": \"None\"}, \"Q\": {\"200\": 0.28571428571428575, \"500\": 0.7777777777777778, \"100\": \"None\", \"600\": \"None\"}, \"BM\": {\"200\": 0.125, \"500\": 0.27450980392156854, \"100\": \"None\", \"600\": 0.0}, \"AM\": {\"200\": -9, \"500\": -1, \"100\": 11, \"600\": -1}, \"OOC\": {\"200\": 0.5669467095138409, \"500\": 0.4082482904638631, \"100\": \"None\", \"600\": \"None\"}, \"TON\": {\"200\": 13, \"500\": 18, \"100\": 9, \"600\": 20}, \"BCD\": {\"200\": 0.225, \"500\": 0.025, \"100\": 0.275, \"600\": 0.025}, \"GM\": {\"200\": 0.5303300858899106, \"500\": 0.5601120336112039, \"100\": \"None\", \"600\": 0.0}, \"OP\": {\"200\": 0.1166666666666667, \"500\": 0.373076923076923, \"100\": \"None\", \"600\": -0.050000000000000044}, \"P\": {\"200\": 16, \"500\": 3, \"100\": 0, \"600\": 1}, \"RACCU\": {\"200\": 0.33062499999999995, \"500\": 0.015625, \"100\": 0.07562500000000001, \"600\": 0.0006250000000000001}}, \"Imbalanced\": true, \"Prob-Vector\": null, \"Predict-Vector\": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], \"Transpose\": false, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]], \"Actual-Vector\": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200]}\n" ] } ], @@ -603,7 +603,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{\"Predict-Vector\": null, \"Sample-Weight\": null, \"Digit\": 5, \"Actual-Vector\": null, \"Transpose\": false, \"Prob-Vector\": null, \"Imbalanced\": true, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]]}\n" + "{\"Digit\": 5, \"Sample-Weight\": null, \"Imbalanced\": true, \"Prob-Vector\": null, \"Predict-Vector\": null, \"Transpose\": false, \"Matrix\": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]], \"Actual-Vector\": null}\n" ] } ], diff --git a/Document/Example4_files/cm.obj b/Document/Example4_files/cm.obj index c2b707b2..d14b563f 100644 --- a/Document/Example4_files/cm.obj +++ b/Document/Example4_files/cm.obj @@ -1 +1 @@ -{"Predict-Vector": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], "Sample-Weight": null, "Digit": 5, "Actual-Vector": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200], "Transpose": false, "Prob-Vector": null, "Imbalanced": true, "Matrix": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]]} \ No newline at end of file +{"Digit": 5, "Sample-Weight": null, "Imbalanced": true, "Prob-Vector": null, "Predict-Vector": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], "Transpose": false, "Matrix": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]], "Actual-Vector": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200]} \ No newline at end of file diff --git a/Document/Example4_files/cm_no_vectors.obj b/Document/Example4_files/cm_no_vectors.obj index a935feca..b4cbe990 100644 --- a/Document/Example4_files/cm_no_vectors.obj +++ b/Document/Example4_files/cm_no_vectors.obj @@ -1 +1 @@ -{"Predict-Vector": null, "Sample-Weight": null, "Digit": 5, "Actual-Vector": null, "Transpose": false, "Prob-Vector": null, "Imbalanced": true, "Matrix": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]]} \ No newline at end of file +{"Digit": 5, "Sample-Weight": null, "Imbalanced": true, "Prob-Vector": null, "Predict-Vector": null, "Transpose": false, "Matrix": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 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"None", "Overall RACC": 0.29500000000000004}, "Digit": 5, "Sample-Weight": null, "Class-Stat": {"IS": {"200": 0.09953567355091428, "500": 1.736965594166206, "100": "None", "600": "None"}, "PLRI": {"200": "Poor", "500": "Fair", "100": "None", "600": "None"}, "MCCI": {"200": "Negligible", "500": "Weak", "100": "None", "600": "None"}, "F2": {"200": 0.4225352112676056, "500": 0.35714285714285715, "100": 0.0, "600": 0.0}, "BB": {"200": 0.375, "500": 0.3333333333333333, "100": 0.0, "600": 0.0}, "dInd": {"200": 0.673145600891813, "500": 0.6692567908186672, "100": "None", "600": 1.0}, "PPV": {"200": 0.8571428571428571, "500": 0.5, "100": 0.0, "600": "None"}, "AGM": {"200": 0.5669417382415922, "500": 0.7351956938438939, "100": "None", "600": 0}, "FN": {"200": 10, "100": 0, "500": 2, "600": 1}, "G": {"200": 0.5669467095138409, "500": 0.408248290463863, "100": "None", "600": "None"}, "J": {"200": 0.35294117647058826, "500": 0.25, "100": 0.0, "600": 0.0}, "FOR": {"200": 0.7692307692307692, "500": 0.11111111111111116, "100": 0.0, "600": 0.050000000000000044}, "PLR": {"200": 1.5, "500": 5.666666666666665, "100": "None", "600": "None"}, "TOP": {"200": 7, "500": 2, "100": 11, "600": 0}, "DPI": {"200": "Poor", "500": "Poor", "100": "None", "600": "None"}, "Y": {"200": 0.125, "500": 0.27450980392156854, "100": "None", "600": 0.0}, "IBA": {"200": 0.17578125, "500": 0.1230296039984621, "100": "None", "600": 0.0}, "LS": {"200": 1.0714285714285714, "500": 3.3333333333333335, "100": "None", "600": "None"}, "ACC": {"200": 0.45, "500": 0.85, "100": 0.45, "600": 0.95}, "TN": {"200": 3, "100": 9, "500": 16, "600": 19}, "FPR": {"200": 0.25, "500": 0.05882352941176472, "100": 0.55, "600": 0.0}, "F0.5": {"200": 0.6818181818181818, "500": 0.45454545454545453, "100": 0.0, "600": 0.0}, "RACC": {"200": 0.28, "500": 0.015, "100": 0.0, "600": 0.0}, "sInd": {"200": 0.5240141808835057, "500": 0.5267639848569737, "100": "None", "600": 0.29289321881345254}, "NLR": {"200": 0.8333333333333334, "500": 0.7083333333333334, "100": "None", "600": 1.0}, "AUC": {"200": 0.5625, "500": 0.6372549019607843, "100": "None", "600": 0.5}, "OC": {"200": 0.8571428571428571, "500": 0.5, "100": "None", "600": "None"}, "TNR": {"200": 0.75, "500": 0.9411764705882353, "100": 0.45, "600": 1.0}, "TPR": {"200": 0.375, "500": 0.3333333333333333, "100": "None", "600": 0.0}, "FNR": {"200": 0.625, "500": 0.6666666666666667, "100": "None", "600": 1.0}, "MCEN": {"200": 0.3739448088748241, "500": 0.5802792108518123, "100": 0.3349590631259315, "600": 0.0}, "F1": {"200": 0.5217391304347826, "500": 0.4, "100": 0.0, "600": 0.0}, "ERR": {"200": 0.55, "500": 0.15000000000000002, "100": 0.55, "600": 0.050000000000000044}, "MCC": {"200": 0.10482848367219183, "500": 0.32673201960653564, "100": "None", "600": "None"}, "GI": {"200": 0.125, "500": 0.27450980392156854, "100": "None", "600": 0.0}, "NLRI": {"200": "Negligible", "500": "Negligible", "100": "None", "600": "Negligible"}, "POP": {"200": 20, "500": 20, "100": 20, "600": 20}, "N": {"200": 4, "500": 17, "100": 20, "600": 19}, "MK": {"200": 0.08791208791208782, "500": 0.38888888888888884, "100": 0.0, "600": "None"}, "AGF": {"200": 0.33642097801219245, "500": 0.5665926996700735, "100": 0.0, "600": 0.0}, "DP": {"200": 0.1407391082701595, "500": 0.49789960499474867, "100": "None", "600": "None"}, "NPV": {"200": 0.23076923076923078, "500": 0.8888888888888888, "100": 1.0, "600": 0.95}, "AUPR": {"200": 0.6160714285714286, "500": 0.41666666666666663, "100": "None", "600": "None"}, "FDR": {"200": 0.1428571428571429, "500": 0.5, "100": 1.0, "600": "None"}, "TP": {"200": 6, "100": 0, "500": 1, "600": 0}, "HD": {"200": 11, "500": 3, "100": 11, "600": 1}, "DOR": {"200": 1.7999999999999998, "500": 7.999999999999997, "100": "None", "600": "None"}, "AUCI": {"200": "Poor", "500": "Fair", "100": "None", "600": "Poor"}, "CEN": {"200": 0.3570795472009597, "500": 0.5389466410223563, "100": 0.3349590631259315, "600": 0.0}, "PRE": {"200": 0.8, "500": 0.15, "100": 0.0, "600": 0.05}, "FP": {"200": 1, "100": 11, "500": 1, "600": 0}, "QI": {"200": "Weak", "500": "Strong", "100": "None", "600": "None"}, "ICSI": {"200": 0.2321428571428572, "500": -0.16666666666666674, "100": "None", "600": "None"}, "Q": {"200": 0.28571428571428575, "500": 0.7777777777777778, "100": "None", "600": "None"}, "BM": {"200": 0.125, "500": 0.27450980392156854, "100": "None", "600": 0.0}, "AM": {"200": -9, "500": -1, "100": 11, "600": -1}, "OOC": {"200": 0.5669467095138409, "500": 0.4082482904638631, "100": "None", "600": "None"}, "TON": {"200": 13, "500": 18, "100": 9, "600": 20}, "BCD": {"200": 0.225, "500": 0.025, "100": 0.275, "600": 0.025}, "GM": {"200": 0.5303300858899106, "500": 0.5601120336112039, "100": "None", "600": 0.0}, "OP": {"200": 0.1166666666666667, "500": 0.373076923076923, "100": "None", "600": -0.050000000000000044}, "P": {"200": 16, "500": 3, "100": 0, "600": 1}, "RACCU": {"200": 0.33062499999999995, "500": 0.015625, "100": 0.07562500000000001, "600": 0.0006250000000000001}}, "Imbalanced": true, "Prob-Vector": null, "Predict-Vector": [100, 200, 200, 100, 100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 100, 500, 200], "Transpose": false, "Matrix": [[100, [[200, 0], [500, 0], [100, 0], [600, 0]]], [200, [[200, 6], [500, 1], [100, 9], [600, 0]]], [500, [[200, 1], [500, 1], [100, 1], [600, 0]]], [600, [[200, 0], [500, 0], [100, 1], [600, 0]]]], "Actual-Vector": [600, 200, 200, 200, 200, 200, 200, 200, 500, 500, 500, 200, 200, 200, 200, 200, 200, 200, 200, 200]} \ No newline at end of file diff --git a/Document/Example6.ipynb b/Document/Example6.ipynb index ec39a34a..87a168a9 100644 --- a/Document/Example6.ipynb +++ b/Document/Example6.ipynb @@ -88,11 +88,11 @@ "Class2 0.04762 0.95238 \n", "\n", "\n", - "ACC: {'Class2': 0.9976333515383216, 'Class1': 0.9976333515383216}\n", - "MCC: {'Class2': 0.9378574017402594, 'Class1': 0.9378574017402594}\n", - "CEN: {'Class2': 0.30489006849060607, 'Class1': 0.012858728415908176}\n", - "MCEN: {'Class2': 0.46949279678726225, 'Class1': 0.023280122318969122}\n", - "DP: {'Class2': 2.276283896527635, 'Class1': 2.276283896527635}\n", + "ACC: {'Class1': 0.9976333515383216, 'Class2': 0.9976333515383216}\n", + "MCC: {'Class1': 0.9378574017402594, 'Class2': 0.9378574017402594}\n", + "CEN: {'Class1': 0.012858728415908176, 'Class2': 0.30489006849060607}\n", + "MCEN: {'Class1': 0.023280122318969122, 'Class2': 0.46949279678726225}\n", + "DP: {'Class1': 2.276283896527635, 'Class2': 2.276283896527635}\n", "Kappa: 0.9377606597584491\n", "RCI: 0.8682877002417864\n", "SOA1: Almost Perfect\n" @@ -142,11 +142,11 @@ "Class2 0.95238 0.04762 \n", "\n", "\n", - "ACC: {'Class2': 0.982098458478369, 'Class1': 0.982098458478369}\n", - "MCC: {'Class2': 0.13048897476798949, 'Class1': 0.13048897476798949}\n", - "CEN: {'Class2': 0.4655917826576813, 'Class1': 0.06481573363174531}\n", - "MCEN: {'Class2': 0.4264929996758212, 'Class1': 0.11078640690031397}\n", - "DP: {'Class2': 0.864594924328404, 'Class1': 0.864594924328404}\n", + "ACC: {'Class1': 0.982098458478369, 'Class2': 0.982098458478369}\n", + "MCC: {'Class1': 0.13048897476798949, 'Class2': 0.13048897476798949}\n", + "CEN: {'Class1': 0.06481573363174531, 'Class2': 0.4655917826576813}\n", + "MCEN: {'Class1': 0.11078640690031397, 'Class2': 0.4264929996758212}\n", + "DP: {'Class1': 0.864594924328404, 'Class2': 0.864594924328404}\n", "Kappa: 0.08122239707598865\n", "RCI: 0.022375346499017443\n", "SOA1: Slight\n" @@ -196,11 +196,11 @@ "Class2 0.04762 0.95238 \n", "\n", "\n", - "ACC: {'Class2': 0.019661387220098307, 'Class1': 0.019661387220098307}\n", - "MCC: {'Class2': -0.13000800945464058, 'Class1': -0.13000800945464058}\n", - "CEN: {'Class2': 0.06103563616795208, 'Class1': 0.014927427128936136}\n", - "MCEN: {'Class2': 0.03655796690365652, 'Class1': 0.01281422838054554}\n", - "DP: {'Class2': -0.8416930356875597, 'Class1': -0.8416930356875597}\n", + "ACC: {'Class1': 0.019661387220098307, 'Class2': 0.019661387220098307}\n", + "MCC: {'Class1': -0.13000800945464058, 'Class2': -0.13000800945464058}\n", + "CEN: {'Class1': 0.014927427128936136, 'Class2': 0.06103563616795208}\n", + "MCEN: {'Class1': 0.01281422838054554, 'Class2': 0.03655796690365652}\n", + "DP: {'Class1': -0.8416930356875597, 'Class2': -0.8416930356875597}\n", "Kappa: -0.0017678372492452412\n", "RCI: 0.02192606003351106\n", "SOA1: Poor\n" @@ -261,11 +261,11 @@ "Class4 0.0 0.0 2e-05 0.99998 \n", "\n", "\n", - "ACC: {'Class3': 0.9999250299880048, 'Class4': 0.9999500199920032, 'Class2': 0.9999500199920032, 'Class1': 0.9999750099960016}\n", - "MCC: {'Class3': 0.7302602381427055, 'Class4': 0.9333083339583177, 'Class2': 0.7999750068731099, 'Class1': 0.8944160139432883}\n", - "CEN: {'Class3': 0.3649884090288471, 'Class4': 0.0001575200922489127, 'Class2': 0.25701944178769376, 'Class1': 0.13625493172565745}\n", - "MCEN: {'Class3': 0.4654427710721536, 'Class4': 0.00029569133318617423, 'Class2': 0.3333333333333333, 'Class1': 0.17964888034078544}\n", - "DP: {'Class3': 2.7032690544190636, 'Class4': 3.1691421556058055, 'Class2': 2.869241573973406, 'Class1': 'None'}\n", + "ACC: {'Class4': 0.9999500199920032, 'Class1': 0.9999750099960016, 'Class2': 0.9999500199920032, 'Class3': 0.9999250299880048}\n", + "MCC: {'Class4': 0.9333083339583177, 'Class1': 0.8944160139432883, 'Class2': 0.7999750068731099, 'Class3': 0.7302602381427055}\n", + "CEN: {'Class4': 0.0001575200922489127, 'Class1': 0.13625493172565745, 'Class2': 0.25701944178769376, 'Class3': 0.3649884090288471}\n", + "MCEN: {'Class4': 0.00029569133318617423, 'Class1': 0.17964888034078544, 'Class2': 0.3333333333333333, 'Class3': 0.4654427710721536}\n", + "DP: {'Class4': 3.1691421556058055, 'Class1': 'None', 'Class2': 2.869241573973406, 'Class3': 2.7032690544190636}\n", "Kappa: 0.8666333383326446\n", "RCI: 0.8711441699127427\n", "SOA1: Almost Perfect\n" @@ -324,11 +324,11 @@ "Class4 0.25 0.25 0.25 0.25 \n", "\n", "\n", - "ACC: {'Class3': 0.625, 'Class4': 0.625, 'Class2': 0.625, 'Class1': 0.625}\n", - "MCC: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", - "CEN: {'Class3': 0.8704188162777186, 'Class4': 0.8704188162777186, 'Class2': 0.8704188162777186, 'Class1': 0.8704188162777186}\n", - "MCEN: {'Class3': 0.9308855421443073, 'Class4': 0.9308855421443073, 'Class2': 0.9308855421443073, 'Class1': 0.9308855421443073}\n", - "DP: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", + "ACC: {'Class4': 0.625, 'Class1': 0.625, 'Class2': 0.625, 'Class3': 0.625}\n", + "MCC: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", + "CEN: {'Class4': 0.8704188162777186, 'Class1': 0.8704188162777186, 'Class2': 0.8704188162777186, 'Class3': 0.8704188162777186}\n", + "MCEN: {'Class4': 0.9308855421443073, 'Class1': 0.9308855421443073, 'Class2': 0.9308855421443073, 'Class3': 0.9308855421443073}\n", + "DP: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", "Kappa: 0.0\n", "RCI: 0.0\n", "SOA1: Slight\n" @@ -387,13 +387,13 @@ "Class4 0.76923 0.07692 0.07692 0.07692 \n", "\n", "\n", - "ACC: {'Class3': 0.76, 'Class4': 0.4, 'Class2': 0.76, 'Class1': 0.4}\n", - "MCC: {'Class3': 0.10714285714285714, 'Class4': -0.2358640882624316, 'Class2': 0.10714285714285714, 'Class1': -0.2358640882624316}\n", - "CEN: {'Class3': 0.8704188162777186, 'Class4': 0.6392779429225796, 'Class2': 0.8704188162777186, 'Class1': 0.6392779429225794}\n", - "MCEN: {'Class3': 0.9308855421443073, 'Class4': 0.647512271542988, 'Class2': 0.9308855421443073, 'Class1': 0.647512271542988}\n", - "DP: {'Class3': 0.16596653499824943, 'Class4': -0.3319330699964992, 'Class2': 0.16596653499824943, 'Class1': -0.33193306999649924}\n", - "Kappa: -0.07361963190184047\n", - "RCI: 0.11603030564493627\n", + "ACC: {'Class4': 0.4, 'Class1': 0.4, 'Class2': 0.76, 'Class3': 0.76}\n", + "MCC: {'Class4': -0.2358640882624316, 'Class1': -0.2358640882624316, 'Class2': 0.10714285714285714, 'Class3': 0.10714285714285714}\n", + "CEN: {'Class4': 0.6392779429225796, 'Class1': 0.6392779429225794, 'Class2': 0.8704188162777186, 'Class3': 0.8704188162777186}\n", + "MCEN: {'Class4': 0.647512271542988, 'Class1': 0.647512271542988, 'Class2': 0.9308855421443073, 'Class3': 0.9308855421443073}\n", + "DP: {'Class4': -0.3319330699964992, 'Class1': -0.33193306999649924, 'Class2': 0.16596653499824943, 'Class3': 0.16596653499824943}\n", + "Kappa: -0.07361963190184051\n", + "RCI: 0.1160303056449364\n", "SOA1: Poor\n" ] } @@ -450,13 +450,13 @@ "Class4 0.76923 0.07692 0.07692 0.07692 \n", "\n", "\n", - "ACC: {'Class3': 0.999400898652022, 'Class4': 0.000998502246630055, 'Class2': 0.999400898652022, 'Class1': 0.000998502246630055}\n", - "MCC: {'Class3': 0.24970032963739885, 'Class4': -0.43266656861311537, 'Class2': 0.24970032963739885, 'Class1': -0.43266656861311537}\n", - "CEN: {'Class3': 0.8704188162777186, 'Class4': 0.0029588592520426657, 'Class2': 0.8704188162777186, 'Class1': 0.0029588592520426657}\n", - "MCEN: {'Class3': 0.9308855421443073, 'Class4': 0.002903385725603509, 'Class2': 0.9308855421443073, 'Class1': 0.002903385725603509}\n", - "DP: {'Class3': 1.6794055876913858, 'Class4': -1.9423127303715728, 'Class2': 1.6794055876913858, 'Class1': -1.9423127303715728}\n", - "Kappa: -0.0003990813465900262\n", - "RCI: 0.5536610475678804\n", + "ACC: {'Class4': 0.000998502246630055, 'Class1': 0.000998502246630055, 'Class2': 0.999400898652022, 'Class3': 0.999400898652022}\n", + "MCC: {'Class4': -0.43266656861311537, 'Class1': -0.43266656861311537, 'Class2': 0.24970032963739885, 'Class3': 0.24970032963739885}\n", + "CEN: {'Class4': 0.0029588592520426657, 'Class1': 0.0029588592520426657, 'Class2': 0.8704188162777186, 'Class3': 0.8704188162777186}\n", + "MCEN: {'Class4': 0.002903385725603509, 'Class1': 0.002903385725603509, 'Class2': 0.9308855421443073, 'Class3': 0.9308855421443073}\n", + "DP: {'Class4': -1.9423127303715728, 'Class1': -1.9423127303715728, 'Class2': 1.6794055876913858, 'Class3': 1.6794055876913858}\n", + "Kappa: -0.0003990813465900263\n", + "RCI: 0.5536610475678805\n", "SOA1: Poor\n" ] } @@ -513,11 +513,11 @@ "Class4 0.25 0.25 0.25 0.25 \n", "\n", "\n", - "ACC: {'Class3': 0.7115384615384616, 'Class4': 0.36538461538461536, 'Class2': 0.7115384615384616, 'Class1': 0.7115384615384616}\n", - "MCC: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", - "CEN: {'Class3': 0.6392779429225794, 'Class4': 0.6522742127953861, 'Class2': 0.6392779429225794, 'Class1': 0.6392779429225794}\n", - "MCEN: {'Class3': 0.647512271542988, 'Class4': 0.7144082229288313, 'Class2': 0.647512271542988, 'Class1': 0.647512271542988}\n", - "DP: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", + "ACC: {'Class4': 0.36538461538461536, 'Class1': 0.7115384615384616, 'Class2': 0.7115384615384616, 'Class3': 0.7115384615384616}\n", + "MCC: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", + "CEN: {'Class4': 0.6522742127953861, 'Class1': 0.6392779429225794, 'Class2': 0.6392779429225794, 'Class3': 0.6392779429225794}\n", + "MCEN: {'Class4': 0.7144082229288313, 'Class1': 0.647512271542988, 'Class2': 0.647512271542988, 'Class3': 0.647512271542988}\n", + "DP: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", "Kappa: 0.0\n", "RCI: 0.0\n", "SOA1: Slight\n" @@ -576,11 +576,11 @@ "Class4 0.25 0.25 0.25 0.25 \n", "\n", "\n", - "ACC: {'Class3': 0.7499500149955014, 'Class4': 0.25014995501349596, 'Class2': 0.7499500149955014, 'Class1': 0.7499500149955014}\n", - "MCC: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", - "CEN: {'Class3': 0.0029588592520426657, 'Class4': 0.539296694603886, 'Class2': 0.0029588592520426657, 'Class1': 0.0029588592520426657}\n", - "MCEN: {'Class3': 0.002903385725603509, 'Class4': 0.580710610324597, 'Class2': 0.002903385725603509, 'Class1': 0.002903385725603509}\n", - "DP: {'Class3': 0.0, 'Class4': 0.0, 'Class2': 0.0, 'Class1': 0.0}\n", + "ACC: {'Class4': 0.25014995501349596, 'Class1': 0.7499500149955014, 'Class2': 0.7499500149955014, 'Class3': 0.7499500149955014}\n", + "MCC: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", + "CEN: {'Class4': 0.539296694603886, 'Class1': 0.0029588592520426657, 'Class2': 0.0029588592520426657, 'Class3': 0.0029588592520426657}\n", + "MCEN: {'Class4': 0.580710610324597, 'Class1': 0.002903385725603509, 'Class2': 0.002903385725603509, 'Class3': 0.002903385725603509}\n", + "DP: {'Class4': 0.0, 'Class1': 0.0, 'Class2': 0.0, 'Class3': 0.0}\n", "Kappa: 0.0\n", "RCI: 0.0\n", "SOA1: Slight\n" diff --git a/Document/Example7.ipynb b/Document/Example7.ipynb index f35d23b3..76f41368 100644 --- a/Document/Example7.ipynb +++ b/Document/Example7.ipynb @@ -60,7 +60,22 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Keyring is skipped due to an exception: invalid syntax (core.py, line 48)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Keyring is skipped due to an exception: invalid syntax (core.py, line 48)\n" + ] + } + ], "source": [ "!{sys.executable} -m pip -q -q install seaborn;\n", "!{sys.executable} -m pip -q -q install pandas;" diff --git a/Document/Example8.ipynb b/Document/Example8.ipynb index 3ef0dca7..24099456 100644 --- a/Document/Example8.ipynb +++ b/Document/Example8.ipynb @@ -55,7 +55,15 @@ "metadata": { "hide_output": true }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Keyring is skipped due to an exception: invalid syntax (core.py, line 48)\n" + ] + } + ], "source": [ "!{sys.executable} -m pip -q -q install matplotlib;" ] diff --git a/Otherfiles/meta.yaml b/Otherfiles/meta.yaml index 9e153c08..0f76a472 100644 --- a/Otherfiles/meta.yaml +++ b/Otherfiles/meta.yaml @@ -1,5 +1,5 @@ {% set name = "pycm" %} -{% set version = "4.0" %} +{% set version = "4.1" %} package: name: {{ name|lower }} diff --git a/Otherfiles/test.html b/Otherfiles/test.html index 29c91105..d20d36a6 100644 --- a/Otherfiles/test.html +++ b/Otherfiles/test.html @@ -21,8 +21,7 @@

    Dataset Type :

  • Balanced

    • Note 1 : Recommended statistics for this type of classification highlighted in aqua

    -

    Note 2 : The recommender system assumes that the input is the result of classification over the whole data rather than just a part of it. -If the confusion matrix is the result of test data classification, the recommendation is not valid.

    +

    Note 2 : The recommendation system assumes the input is the result of classification over the entire dataset, not just a subset. If the confusion matrix is based on test data classification, the recommendation may not be valid.

    Confusion Matrix :

    @@ -787,6 +786,6 @@

    Class Statistics :

    Similarity index
    -

    Generated By PyCM Version 4.0

    +

    Generated By PyCM Version 4.1

    diff --git a/Otherfiles/test.obj b/Otherfiles/test.obj index 4fc44c8c..d3781572 100644 --- a/Otherfiles/test.obj +++ b/Otherfiles/test.obj @@ -1 +1 @@ -{"Predict-Vector": null, "Prob-Vector": null, "Imbalanced": false, "Matrix": [["L1", [["L2", 0], ["L3", 2], ["L1", 3]]], ["L2", [["L2", 1], ["L3", 1], ["L1", 0]]], ["L3", [["L2", 2], ["L3", 3], ["L1", 0]]]], "Digit": 5, "Transpose": true, "Actual-Vector": null, "Sample-Weight": null} \ No newline at end of file +{"Actual-Vector": null, "Predict-Vector": null, "Prob-Vector": null, "Transpose": true, "Digit": 5, "Sample-Weight": null, "Matrix": [["L1", [["L1", 3], ["L2", 0], ["L3", 2]]], ["L2", [["L1", 0], ["L2", 1], ["L3", 1]]], ["L3", [["L1", 0], ["L2", 2], ["L3", 3]]]], "Imbalanced": false} \ No newline at end of file diff --git a/Otherfiles/version_check.py b/Otherfiles/version_check.py index 33072794..b1c350cf 100644 --- a/Otherfiles/version_check.py +++ b/Otherfiles/version_check.py @@ -4,7 +4,7 @@ import sys import codecs Failed = 0 -PYCM_VERSION = "4.0" +PYCM_VERSION = "4.1" SETUP_ITEMS = [ diff --git a/README.md b/README.md index e694f1df..3359085e 100644 --- a/README.md +++ b/README.md @@ -75,10 +75,10 @@ PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scie ### PyPI - Check [Python Packaging User Guide](https://packaging.python.org/installing/) -- Run `pip install pycm==4.0` +- Run `pip install pycm==4.1` ### Source code -- Download [Version 4.0](https://github.com/sepandhaghighi/pycm/archive/v4.0.zip) or [Latest Source](https://github.com/sepandhaghighi/pycm/archive/dev.zip) +- Download [Version 4.1](https://github.com/sepandhaghighi/pycm/archive/v4.1.zip) or [Latest Source](https://github.com/sepandhaghighi/pycm/archive/dev.zip) - Run `pip install .` ### Conda @@ -484,6 +484,13 @@ PyCM can be used online in interactive Jupyter Notebooks via the Binder or Colab Python Software Foundation +Some parts of the infrastructure for this project are supported by: +

    + + DigitalOcean + +

    + ## Cite If you use PyCM in your research, we would appreciate citations to the following paper : diff --git a/SECURITY.md b/SECURITY.md index e6103a47..6d62d43f 100644 --- a/SECURITY.md +++ b/SECURITY.md @@ -4,8 +4,8 @@ | Version | Supported | | ------------- | ------------------ | -| 4.0 | :white_check_mark: | -| < 4.0 | :x: | +| 4.1 | :white_check_mark: | +| < 4.1 | :x: | ## Reporting a vulnerability diff --git a/pycm/params.py b/pycm/params.py index 20ea9e11..7c927737 100644 --- a/pycm/params.py +++ b/pycm/params.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- """Parameters and constants.""" -PYCM_VERSION = "4.0" +PYCM_VERSION = "4.1" OVERVIEW = ''' diff --git a/setup.py b/setup.py index f34e4ca0..7b88af3d 100644 --- a/setup.py +++ b/setup.py @@ -36,14 +36,14 @@ def read_description(): setup( name='pycm', packages=['pycm'], - version='4.0', + version='4.1', description='Multi-class confusion matrix library in Python', long_description=read_description(), long_description_content_type='text/markdown', author='PyCM Development Team', author_email='info@pycm.io', url='https://github.com/sepandhaghighi/pycm', - download_url='https://github.com/sepandhaghighi/pycm/tarball/v4.0', + download_url='https://github.com/sepandhaghighi/pycm/tarball/v4.1', keywords="confusion-matrix python3 python machine_learning ML", project_urls={ 'Webpage': 'https://www.pycm.io',