SciKit Learn §

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• Introdução

Módulo “model selection” §

• Grid Search CV
• K-Fold
• train_test_split
• cross-val-score

Módulo “pre-processing” §

Standard Scaler §

• fit_transform
• Label Encoder
  • fit_transform
• One-Hot Encoder
  • fit_transform
• PolynomialFeatures

Módulo “naive bayes” §

GaussianNB §

• Principais atributos
• fit
• predict

Módulo “metrics” §

• accurancy_score
• confusion_matrix
• classification_report

Módulo “tree” §

• Decision Tree Classifier
• Decision Tree Regressor
• plot_tree

Módulo “ensemble” §

• Random Forest Classifier
• Random Forest Regressor
• ExtraTreesClassifier

Módulo “neighbors” §

• K-Neighbors Classifier

Módulo “svm” §

• SVC
• SVR

Módulo “neural network” §

• MLP Classifier

Módulo “liner model” §

• Linear Regression

Módulo “cluster” §

• KMeans
• AgglomerativeClustering
• DBSCAN

Módulo “datasets” §

• make_blobs

Módulo “decomposition” §

• PCA
• KernelPCA

Módulo “feature-selection” §

• VarianceThreshold

Módulo “discriminant-analysis” §

• LinearDiscriminantAnalysis