Remove and ignore results.
parent
0f8f0b0fb6
commit
7b5db88f1d
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@ -16,6 +16,7 @@ __pycache__/
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/data/30min*
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/data/30min*
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/presentation/*scores.csv
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/presentation/*scores.csv
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/presentation/Results.ods
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/presentation/Results.ods
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/presentation/results/
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.Rproj.user
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.Rproj.user
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.Rhistory
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.Rhistory
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/presentation/*.nb.html
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/presentation/*.nb.html
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@ -1,29 +0,0 @@
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method,metric,max,mean
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Dummy,test_accuracy,0.8557046979865772,0.8548446932649828
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Dummy,test_average_precision,0.1457286432160804,0.14515530673501736
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Dummy,test_recall,0.0,0.0
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Dummy,test_f1,0.0,0.0
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logistic_reg,test_accuracy,0.8640939597315436,0.8504895843872606
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logistic_reg,test_average_precision,0.44363425265068757,0.37511495347389834
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logistic_reg,test_recall,0.3023255813953488,0.24266238973536486
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logistic_reg,test_f1,0.3909774436090226,0.318943511424051
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svc,test_accuracy,0.8557046979865772,0.8548446932649828
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svc,test_average_precision,0.44514416839823046,0.4068200938341621
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svc,test_recall,0.0,0.0
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svc,test_f1,0.0,0.0
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gaussian_naive_bayes,test_accuracy,0.7684563758389261,0.7479123806954234
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gaussian_naive_bayes,test_average_precision,0.2534828030085334,0.23379392278901853
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gaussian_naive_bayes,test_recall,0.42528735632183906,0.3924619085805935
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gaussian_naive_bayes,test_f1,0.34285714285714286,0.3107236284017699
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stochastic_gradient_descent,test_accuracy,0.8576214405360134,0.7773610783222601
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stochastic_gradient_descent,test_average_precision,0.3813093757959869,0.3617503752215592
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stochastic_gradient_descent,test_recall,0.686046511627907,0.2822507350975675
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stochastic_gradient_descent,test_f1,0.3652173913043478,0.21849107443075583
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random_forest,test_accuracy,0.9110738255033557,0.9011129472867694
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random_forest,test_average_precision,0.6998372262021191,0.6619275281099584
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random_forest,test_recall,0.4069767441860465,0.35356856455493185
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random_forest,test_f1,0.5691056910569107,0.5078402513053142
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xgboost,test_accuracy,0.9128978224455612,0.9007711937764886
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xgboost,test_average_precision,0.7366643049075349,0.698622165966308
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xgboost,test_recall,0.5287356321839081,0.44346431435445066
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xgboost,test_f1,0.638888888888889,0.5633957169928393
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@ -1,29 +0,0 @@
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method,metric,max,mean
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Dummy,test_accuracy,1.0,0.8524114578096439
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Dummy,test_average_precision,0.7,0.14758854219035614
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Dummy,test_recall,0.0,0.0
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Dummy,test_f1,0.0,0.0
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logistic_reg,test_accuracy,0.9824561403508771,0.8445351955631311
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logistic_reg,test_average_precision,1.0,0.44605167668563583
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logistic_reg,test_recall,1.0,0.25353566685532386
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logistic_reg,test_f1,0.823529411764706,0.27951926390778625
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svc,test_accuracy,1.0,0.8524114578096439
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svc,test_average_precision,0.9612401707068228,0.44179454944271934
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svc,test_recall,0.0,0.0
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svc,test_f1,0.0,0.0
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gaussian_naive_bayes,test_accuracy,0.9,0.7491301746887129
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gaussian_naive_bayes,test_average_precision,0.9189430193277607,0.2833170327386991
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gaussian_naive_bayes,test_recall,1.0,0.3743761174081108
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gaussian_naive_bayes,test_f1,0.7000000000000001,0.2698456659235668
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stochastic_gradient_descent,test_accuracy,1.0,0.7926428596764739
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stochastic_gradient_descent,test_average_precision,1.0,0.4421948838597582
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stochastic_gradient_descent,test_recall,1.0,0.30156420704502945
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stochastic_gradient_descent,test_f1,0.8148148148148148,0.24088393234361388
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random_forest,test_accuracy,1.0,0.8722158105763481
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random_forest,test_average_precision,1.0,0.49817066323226833
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random_forest,test_recall,1.0,0.18161263127840668
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random_forest,test_f1,1.0,0.2508096532365307
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xgboost,test_accuracy,1.0,0.8812627400277729
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xgboost,test_average_precision,1.0,0.5505695112208401
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xgboost,test_recall,1.0,0.2896161238315027
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xgboost,test_f1,0.9411764705882353,0.36887408735855665
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