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best algorithm for classification
whatever by
Wide-eyed Whale
on May 23 2020
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Accuracy of XGBClassifier is 95.55Confusion Matrix of XGBClassifier is [[ 9 0 0] [ 0 15 1] [ 0 1 19]]Accuracy of SVC is 95.55Confusion Matrix of SVC is [[ 9 0 0] [ 0 16 0] [ 0 2 18]]Accuracy of DecisionTreeClassifier is 88.88Confusion Matrix of DecisionTreeClassifier is [[ 9 0 0] [ 0 15 1] [ 0 4 16]]Accuracy of RandomForestClassifier is 84.44Confusion Matrix of RandomForestClassifier is [[ 9 0 0] [ 0 15 1] [ 0 6 14]]
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best algorithm for classification
python by
Wide-eyed Whale
on May 23 2020
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model1 = xgboost.XGBClassifier()classifiers.append(model1)model2 = svm.SVC()classifiers.append(model2)model3 = tree.DecisionTreeClassifier()classifiers.append(model3)model4 = RandomForestClassifier()classifiers.append(model4)
Source:
medium.com
best algorithm for classification
python by
Wide-eyed Whale
on May 23 2020
Donate
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for clf in classifiers: clf.fit(X_train, y_train) y_pred= clf.predict(X_test) acc = accuracy_score(y_test, y_pred) print("Accuracy of %s is %s"%(clf, acc)) cm = confusion_matrix(y_test, y_pred) print("Confusion Matrix of %s is %s"%(clf, cm)
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