machine learning algorithms

1.Supervised
	1.1 Regression
    	 1.1.1 Linear Regression
         1.1.2 Decision Tree
         1.1.3 Random Forest
		 1.1.4 Neural Network
	1.2 Classification
    	 1.2.1 Logistic Regression
		 1.2.2 Support Vector Machine
		 1.2.3 Naive Bayes
		 1.2.4 Decision Tree, Random Forest, Neural Network
2.Unsupervised
	2.1 Clustering
    2.2 Dimensionality Reduction
	2.3 Principal Component Analysis (PCA)

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4.33

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Lionel Aguero 33605 points

                                    model1 = xgboost.XGBClassifier()classifiers.append(model1)model2 = svm.SVC()classifiers.append(model2)model3 = tree.DecisionTreeClassifier()classifiers.append(model3)model4 = RandomForestClassifier()classifiers.append(model4)

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4.33 (3 Votes)

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Awgiedawgie 440220 points

                                    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]]

Thank you! 6

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