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Evaluation for classification dataitgirls3 Instructor Sunmi Yoon
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Confusion Matrix
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https://sumniya.tistory.com/26
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Evaluation Metrics from Confusion Matrix
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https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62
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Precision(ب), PPV(Positive Predictive Value) ݽ؛ TrueۄҊ ࠙ܨೠ Ѫ ী, पઁ Trueੋ Ѫ ࠺ਯ Recall(അਯ), Sensitivity, hit rate पઁ True ী ݽ؛ True۽ ࠙ܨೠ ࠺ਯ “Precision݅ न҃ਸ ॳݶ ݽ؛ ੋ࢝೧Ҋ, Recall݅ न҃ॳݶ ݽ؛ ಌ” ܳ ࢤп೧ࠁࣁਃ.
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Accuracy TP, TNਸ ݽف Ҋ۰ೞח . Label ࠛӐഋ बೡ ٸী ࢎਊਸ ೧ঠ פ. F1 Score Precisionҗ Recall ઑചಣӐ Label ࠛӐഋ बೡ ٸী ݽ؛ ࢿמਸ ഛೞѱ ಣоೡ ࣻ णפ. Label ࠛӐഋ बೡ ٸী, Accuracyח ۽ࢲ न܉ࢿਸ णפ. ਬܳ ࢤп ೧ ࠁࣁਃ.
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https://sumniya.tistory.com/26 ৵ ࣿಣӐ ইפҊ ઑചಣӐੋо?
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ઑӘ݅ ؊ о ࠇद
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https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62 द Ӓܿਵ۽ جই৬ࢲ, ଘ ফܳ बਵ۽ ࢤп೮
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https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62 द Ӓܿਵ۽ جই৬ࢲ, ߣূ ফب э ࢤпೞݶࢲ ࠇद (Әࠗఠ ഁтܾ ࣻ )
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN Precision Positive Predictive Value ࠙ܨ Ѿҗ(ݽ؛)ਸ बਵ۽
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN Negative Predictive Value ࠙ܨ Ѿҗ(ݽ؛)ਸ बਵ۽
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN Recall Sensitivity True Positive Rate ਸ बਵ۽
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN ਸ बਵ۽ False Positive Rate
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN ਸ बਵ۽ Specificity True Negative Rate
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN ਸ बਵ۽ Fall-out rate False Positive Rate
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https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62 Ѧ ೞҊ ೮ભ. ߣূ ফب э ࢤпೞݶࢲ ࠇद (Әࠗఠ ഁтܾ ࣻ )
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN ? TP ब ٜ ܻೞݶ, ?
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TRUE FALSE ࠙ܨѾҗ TRUE TP FP FALSE FN TN TN ब ٜ ? ܻೞݶ, ?
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ഁтܻભ? ਗې Ӓ۠Ѣਃ
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ӝୡח ೮ਵפө ઑӘ݅ ؊ ೧ ࠇद.
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Confusion Matrix with Histogram
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https://www.medcalc.org/manual/roc-curves.php Criterion, Threshold য়ܲଃ Distribution Actual True, ৽ଃ Actual False. Threshold ਤ۽ח ݽف True۽ ஏೞח ݽ؛ Ҋ о೮ਸ ٸ,
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https://www.medcalc.org/manual/roc-curves.php Thresholdܳ ӓױਵ۽ ஏ ز दெࠇद. যڃ ੌ ੌযաաਃ? Precision: Recall: Specificity: Fall-out:
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https://www.medcalc.org/manual/roc-curves.php Thresholdܳ ӓױਵ۽ ஏ ز दெࠇद. যڃ ੌ ੌযաաਃ? True positive rate: True negative rate:
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https://www.medcalc.org/manual/roc-curves.php ߣূ ߈۽ ز दெࠇद. যڃ ੌ ੌযաաਃ? True positive rate: True negative rate:
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Specificity৬ Sensitivity ҙ҅ https://www.medcalc.org/manual/roc-curves.php
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ROC(Receiver Operating Characteristic) curve
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рױೞѱח, Sensitivity৬ 1-Specificityܳ п ୷ਵ۽ ೞח 2ରਗ Ӓې https://www.medcalc.org/manual/roc-curves.php AUC (Area Under Curve)
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рױೞѱח, Sensitivity৬ 1-Specificityܳ п ୷ਵ۽ ೞח 2ରਗ Ӓې https://www.medcalc.org/manual/roc-curves.php Actual True৬ Actual False distribution ৮߷ೞѱ эਸ ٸ (feature class ߸߹מ۱ হ) ROC curveח 45ب пب ࢶ
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рױೞѱח, Sensitivity৬ 1-Specificityܳ п ୷ਵ۽ ೞח 2ରਗ Ӓې https://www.medcalc.org/manual/roc-curves.php Actual True৬ Actual False distribution Ҁח হ ৮߷ೞѱ ܻ࠙ ؼ ٸ ROC ழ࠳ (feature class ߸߹ מ۱ ৮߷) ROC ழ࠳о ઝ࢚ױী оөࣻ۾ feature class ߸߹ מ۱ જҊ ೡ ࣻ .
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ROC(Receiver Operating Characteristic) curve with Machine Learning
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Classifierܳ ݅ٚח Ѥ, ف ѐ histogramਸ ӒܻҊ Thresholdܳ ೞח Ѫ https://www.medcalc.org/manual/roc-curves.php
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https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html#sphx-glr-auto-examples-model-selection-plot-roc-py Histogramਸ Ӓ۷ח Ѥ ROC ழ࠳ܳ Ӓܾ ࣻ ח Ѫ!
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https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html#sphx-glr-auto-examples-model-selection-plot-roc-py ROC ழ࠳ܳ Ӓܾ ࣻ ח Ѥ ৈ۞ ROC ழ࠳ р ࠺Үܳ ా೧ જ ࢿמ ݽ؛ਸ ইյ ࣻ ח Ѫ!
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AUCо = ݽ؛ ҅ೠ probabilityܳ ߄ఔਵ۽ Ӓܽ histogramٜ ੜ ܻ࠙غয . = ݽ؛ Threshold(Decision BoundaryۄҊب ೠ)ী ؏ хೞ. = উੋ ஏਸ ೠ.
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ݽ؛ ࢶఖী ROC ழ࠳ܳ ഝਊೠ = Decision Boundaryী ࢚ҙহ ؊ જ ݽ؛ਸ ח. = ganziо դ.
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Ӓ۰ࠇद. ؘఠ: titanic ݽ؛ - sklearn.linear_model.LinearRegression - sklearn.linear_model.LogisticRegression - sklearn.tree.DecisionTreeClassifier - sklearn.ensemble.RandomForestClassifier ١ whatever you want - Tree ҅ৌ ݽ؛ ҃ model predict_proba() ݫࣗ٘ܳ ࢎਊೞݶ ഛܫ ҅ ؾ פ. - ীח Thresholdܳ a ݅ఀ ز೧оݴ Sensitivity, Specificityܳ ҅೧ ઝܳ ҳೞ ࣁਃ. - যڌѱ ೞݶ Thresholdܳ ੜ زदఃݶࢲ ROC ઝܳ ନਸ ࣻ ਸөਃ? - ઝٜਸ ಣݶ࢚ী ନযࠁࣁਃ.
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sklearn.metrics.roc_curve ܳ ഝਊ ೧ ࠇद. ؘఠ: titanic ݽ؛ - sklearn.linear_model.LinearRegression - sklearn.linear_model.LogisticRegression - sklearn.tree.DecisionTreeClassifier - sklearn.ensemble.RandomForestClassifier ١ whatever you want ؊ աইоࢲ, - sklearnਸ ਊ೧ AUCب ҅ ೧ࠇद. - ৈ۞ ݽ؛ٜ ࢿמਸ ࠺Ү ೧ ࠇद. - DecisionTreeClassifierܳ ࢎਊ೮؊ۄب, ࢎਊೠ featureо ܰݶ ӒѤ ܲ ݽ؛ੑפ . - ఋఋץ ݈Ҋ, ܲ classification ޙઁীب ഝਊ೧ ࠁࣁਃ.
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