Machinelearning

• Multi-Layer Perceptron Classifier
• Decision Tree Classifier
• Random Forest Classifier
• Pipeline
• Pipeline decomposition
• Multi-output classifier
• Multi-output regressor
• Voting Classifier
• Text Count Vectorizer
• Conditional Probabilty from Categories
• Confusion Matrix
• Learning Curve
• ROC from Probabilities
• Extract Parameters
• Parameter Distribution
• Set Input and Output Names
• Set Parameters
• Isolation Forest
• Group K-fold Cross Validation
• K-fold Cross Validation
• Leave One Group out Cross Validation
• Simple Train-Test Split
• Stratified K-fold cross validation
• Time Series K-fold Based Cross Validation
• Score Cross Validation
• Split Data for Cross Validation
• Features to Images
• Images to Features
• Example datasets
• Export Model
• Import Model
• Generate dataset blobs
• Generate dataset blobs from table
• Generate classification dataset
• Grid Parameter Search
• Randomized Parameter Search
• Simulated Annealing Parameter Search
• Kernel Principal Component Analysis (KPCA)
• Principal Component Analysis (PCA)
• Extract Attributes
• Binarizer
• Categorical Encoder
• Imputer
• Label Binarizer
• Label Encoder
• Max Abs Scaler
• Normalizer
• One-Hot Encoder
• Polynomial Features
• Robust Scaler
• Standard Scaler
• One Class SVM
• Support Vector Classifier
• K-means Clustering
• Mini-batch K-means Clustering
• Kernel Ridge Regression
• Linear Regression
• Logistic Regression
• Epsilon Support Vector Regression
• Decision Function
• Fit
• Fit Texts
• Fit Transform
• Fit Transform Text
• Inverse Transform
• Predict
• Predict Probabilities
• Score
• Select Features from Model
• Transform
• Transform Text