From 1e636ffb3799ac429b1c7e1fd4ad1e7d797dc941 Mon Sep 17 00:00:00 2001 From: Shreyas Date: Wed, 26 Mar 2014 11:52:31 -0700 Subject: [PATCH] started working on classifier report --- docs/classifier_benchmark.md | 1963 ++++++++++++++++++++++++++++++++++ wiki | 2 +- 2 files changed, 1964 insertions(+), 1 deletion(-) create mode 100644 docs/classifier_benchmark.md diff --git a/docs/classifier_benchmark.md b/docs/classifier_benchmark.md new file mode 100644 index 0000000..3e429b8 --- /dev/null +++ b/docs/classifier_benchmark.md @@ -0,0 +1,1963 @@ +Classifying 0 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 0.33 0.50 3 + True 0.60 1.00 0.75 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[1 2] + [0 3]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 0.33 0.33 3 + True 0.33 0.33 0.33 3 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[1 2] + [2 1]] + + + +Classifying 1 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.33 0.40 3 + True 0.50 0.67 0.57 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[1 2] + [1 2]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.25 0.33 0.29 3 + True 0.00 0.00 0.00 3 + +avg / total 0.12 0.17 0.14 6 + + + +Confusion matrix: +[[1 2] + [3 0]] + + + +Classifying 2 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 1.00 0.80 2 + True 1.00 0.75 0.86 4 + +avg / total 0.89 0.83 0.84 6 + + + +Confusion matrix: +[[2 0] + [1 3]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 1.00 0.80 2 + True 1.00 0.75 0.86 4 + +avg / total 0.89 0.83 0.84 6 + + + +Confusion matrix: +[[2 0] + [1 3]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 2 + True 1.00 0.50 0.67 4 + +avg / total 0.83 0.67 0.67 6 + + + +Confusion matrix: +[[2 0] + [2 2]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 2 + True 0.60 0.75 0.67 4 + +avg / total 0.40 0.50 0.44 6 + + + +Confusion matrix: +[[0 2] + [1 3]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 1.00 0.50 2 + True 0.00 0.00 0.00 4 + +avg / total 0.11 0.33 0.17 6 + + + +Confusion matrix: +[[2 0] + [4 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 0.50 0.67 2 + True 0.80 1.00 0.89 4 + +avg / total 0.87 0.83 0.81 6 + + + +Confusion matrix: +[[1 1] + [0 4]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 2 + True 0.60 0.75 0.67 4 + +avg / total 0.40 0.50 0.44 6 + + + +Confusion matrix: +[[0 2] + [1 3]] + + + +Classifying 3 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.20 0.50 0.29 2 + True 0.00 0.00 0.00 4 + +avg / total 0.07 0.17 0.10 6 + + + +Confusion matrix: +[[1 1] + [4 0]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.20 0.50 0.29 2 + True 0.00 0.00 0.00 4 + +avg / total 0.07 0.17 0.10 6 + + + +Confusion matrix: +[[1 1] + [4 0]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 1.00 0.57 2 + True 1.00 0.25 0.40 4 + +avg / total 0.80 0.50 0.46 6 + + + +Confusion matrix: +[[2 0] + [3 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 2 + True 0.50 0.50 0.50 4 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[0 2] + [2 2]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 1.00 0.50 2 + True 0.00 0.00 0.00 4 + +avg / total 0.11 0.33 0.17 6 + + + +Confusion matrix: +[[2 0] + [4 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 1.00 0.50 2 + True 0.00 0.00 0.00 4 + +avg / total 0.11 0.33 0.17 6 + + + +Confusion matrix: +[[2 0] + [4 0]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 2 + True 0.50 0.50 0.50 4 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[0 2] + [2 2]] + + + +Classifying 4 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + + +Classifying 5 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 1.00 1.00 3 + True 1.00 1.00 1.00 3 + +avg / total 1.00 1.00 1.00 6 + + + +Confusion matrix: +[[3 0] + [0 3]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 1.00 1.00 3 + True 1.00 1.00 1.00 3 + +avg / total 1.00 1.00 1.00 6 + + + +Confusion matrix: +[[3 0] + [0 3]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 3 + True 0.40 0.67 0.50 3 + +avg / total 0.20 0.33 0.25 6 + + + +Confusion matrix: +[[0 3] + [1 2]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 1.00 1.00 3 + True 1.00 1.00 1.00 3 + +avg / total 1.00 1.00 1.00 6 + + + +Confusion matrix: +[[3 0] + [0 3]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 0.67 0.80 3 + True 0.75 1.00 0.86 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[2 1] + [0 3]] + + + +Classifying 6 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 0.67 0.67 3 + True 0.67 0.67 0.67 3 + +avg / total 0.67 0.67 0.67 6 + + + +Confusion matrix: +[[2 1] + [1 2]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 0.67 0.67 3 + True 0.67 0.67 0.67 3 + +avg / total 0.67 0.67 0.67 6 + + + +Confusion matrix: +[[2 1] + [1 2]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 0.67 0.67 3 + True 0.67 0.67 0.67 3 + +avg / total 0.67 0.67 0.67 6 + + + +Confusion matrix: +[[2 1] + [1 2]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 0.33 0.33 3 + True 0.33 0.33 0.33 3 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[1 2] + [2 1]] + + + +Classifying 7 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 0.67 0.50 3 + True 0.00 0.00 0.00 3 + +avg / total 0.20 0.33 0.25 6 + + + +Confusion matrix: +[[2 1] + [3 0]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 3 + True 0.00 0.00 0.00 3 + +avg / total 0.25 0.50 0.33 6 + + + +Confusion matrix: +[[3 0] + [3 0]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 3 + True 0.00 0.00 0.00 3 + +avg / total 0.25 0.50 0.33 6 + + + +Confusion matrix: +[[3 0] + [3 0]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 1.00 1.00 3 + True 1.00 1.00 1.00 3 + +avg / total 1.00 1.00 1.00 6 + + + +Confusion matrix: +[[3 0] + [0 3]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 3 + True 0.00 0.00 0.00 3 + +avg / total 0.25 0.50 0.33 6 + + + +Confusion matrix: +[[3 0] + [3 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 0.67 0.50 3 + True 0.00 0.00 0.00 3 + +avg / total 0.20 0.33 0.25 6 + + + +Confusion matrix: +[[2 1] + [3 0]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + + +Classifying 8 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 3 + True 0.00 0.00 0.00 3 + +avg / total 0.25 0.50 0.33 6 + + + +Confusion matrix: +[[3 0] + [3 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 0.33 0.33 3 + True 0.33 0.33 0.33 3 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[1 2] + [2 1]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + + +Classifying 9 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 1.00 0.57 2 + True 1.00 0.25 0.40 4 + +avg / total 0.80 0.50 0.46 6 + + + +Confusion matrix: +[[2 0] + [3 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 1.00 0.50 2 + True 0.00 0.00 0.00 4 + +avg / total 0.11 0.33 0.17 6 + + + +Confusion matrix: +[[2 0] + [4 0]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 1.00 0.57 2 + True 1.00 0.25 0.40 4 + +avg / total 0.80 0.50 0.46 6 + + + +Confusion matrix: +[[2 0] + [3 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 1.00 0.57 2 + True 1.00 0.25 0.40 4 + +avg / total 0.80 0.50 0.46 6 + + + +Confusion matrix: +[[2 0] + [3 1]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 1.00 0.50 2 + True 0.00 0.00 0.00 4 + +avg / total 0.11 0.33 0.17 6 + + + +Confusion matrix: +[[2 0] + [4 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 2 + True 1.00 0.50 0.67 4 + +avg / total 0.83 0.67 0.67 6 + + + +Confusion matrix: +[[2 0] + [2 2]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.40 1.00 0.57 2 + True 1.00 0.25 0.40 4 + +avg / total 0.80 0.50 0.46 6 + + + +Confusion matrix: +[[2 0] + [3 1]] + + + +Classifying 10 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.20 1.00 0.33 1 + True 1.00 0.20 0.33 5 + +avg / total 0.87 0.33 0.33 6 + + + +Confusion matrix: +[[1 0] + [4 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.20 1.00 0.33 1 + True 1.00 0.20 0.33 5 + +avg / total 0.87 0.33 0.33 6 + + + +Confusion matrix: +[[1 0] + [4 1]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.20 1.00 0.33 1 + True 1.00 0.20 0.33 5 + +avg / total 0.87 0.33 0.33 6 + + + +Confusion matrix: +[[1 0] + [4 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 1.00 0.67 1 + True 1.00 0.80 0.89 5 + +avg / total 0.92 0.83 0.85 6 + + + +Confusion matrix: +[[1 0] + [1 4]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.17 1.00 0.29 1 + True 0.00 0.00 0.00 5 + +avg / total 0.03 0.17 0.05 6 + + + +Confusion matrix: +[[1 0] + [5 0]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 1 + True 0.75 0.60 0.67 5 + +avg / total 0.62 0.50 0.56 6 + + + +Confusion matrix: +[[0 1] + [2 3]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.00 0.00 0.00 1 + True 0.80 0.80 0.80 5 + +avg / total 0.67 0.67 0.67 6 + + + +Confusion matrix: +[[0 1] + [1 4]] + + + +Classifying 11 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.67 0.57 3 + True 0.50 0.33 0.40 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[2 1] + [2 1]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 0.33 0.33 3 + True 0.33 0.33 0.33 3 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[1 2] + [2 1]] + + + +Classifying 12 th split of fair apps with unfair app +------------------------------------------------------------------------------- + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=distance) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.50 0.33 0.40 3 + True 0.50 0.67 0.57 3 + +avg / total 0.50 0.50 0.49 6 + + + +Confusion matrix: +[[1 2] + [1 2]] + + +Classifier: + KNeighborsClassifier(algorithm=auto, leaf_size=30, metric=minkowski, + n_neighbors=3, p=2, weights=uniform) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.33 0.33 0.33 3 + True 0.33 0.33 0.33 3 + +avg / total 0.33 0.33 0.33 6 + + + +Confusion matrix: +[[1 2] + [2 1]] + + +Classifier: + GaussianNB() +############################################################################### +Classification report: + precision recall f1-score support + + False 0.75 1.00 0.86 3 + True 1.00 0.67 0.80 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[3 0] + [1 2]] + + +Classifier: + DecisionTreeClassifier(compute_importances=None, criterion=gini, + max_depth=None, max_features=None, min_density=None, + min_samples_leaf=1, min_samples_split=2, random_state=None, + splitter=best) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.60 1.00 0.75 3 + True 1.00 0.33 0.50 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[3 0] + [2 1]] + + +Classifier: + SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0, + kernel=rbf, max_iter=-1, probability=False, random_state=None, + shrinking=True, tol=0.001, verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 0.67 0.67 0.67 3 + True 0.67 0.67 0.67 3 + +avg / total 0.67 0.67 0.67 6 + + + +Confusion matrix: +[[2 1] + [1 2]] + + +Classifier: + NuSVC(cache_size=200, coef0=0.0, degree=3, gamma=0.0, kernel=rbf, max_iter=-1, + nu=0.5, probability=False, random_state=None, shrinking=True, tol=0.001, + verbose=False) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 0.33 0.50 3 + True 0.60 1.00 0.75 3 + +avg / total 0.80 0.67 0.62 6 + + + +Confusion matrix: +[[1 2] + [0 3]] + + +Classifier: + AdaBoostClassifier(algorithm=SAMME, + base_estimator=DecisionTreeClassifier(compute_importances=None, criterion=gini, max_depth=1, + max_features=None, min_density=None, min_samples_leaf=1, + min_samples_split=2, random_state=None, splitter=best), + base_estimator__compute_importances=None, + base_estimator__criterion=gini, base_estimator__max_depth=1, + base_estimator__max_features=None, + base_estimator__min_density=None, + base_estimator__min_samples_leaf=1, + base_estimator__min_samples_split=2, + base_estimator__random_state=None, base_estimator__splitter=best, + learning_rate=1.0, n_estimators=200, random_state=None) +############################################################################### +Classification report: + precision recall f1-score support + + False 1.00 0.67 0.80 3 + True 0.75 1.00 0.86 3 + +avg / total 0.88 0.83 0.83 6 + + + +Confusion matrix: +[[2 1] + [0 3]] + + + diff --git a/wiki b/wiki index 744e002..e509ccc 160000 --- a/wiki +++ b/wiki @@ -1 +1 @@ -Subproject commit 744e00299b7b98e463d2eef85ad48a6d5066e348 +Subproject commit e509ccc4883d612e1e388bee02623a8372935d51