Welcome to GridGain ML Python API documentation!
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Contents:
Basic Information
What is it
Prerequisites
Installation
for end user
for developer
API Specification
Core
Regression
Classification
Clustering
Preprocessing
Model Selection
Inference
Examples of usage
Cache API
Regression
Linear Regression
Decision Tree Regression
KNN Regression
Random Forest Regression
MLP Regression
Classification
Decision Tree Classification
ANN Classification
KNN Classification
LogReg Classification
SVM Classification
Random Forest Classification
MLP Classification
Clustering
KMeans Clustering
GMM Clustering
Preprocessing
Normalization Preprocessing
Binarization Preprocessing
Imputing Preprocessing
One-Hot-Encoding Preprocessing
MinMax Scaling Preprocessing
MaxAbs Scaling Preprocessing
Model Selection
Test/Train Splitting
Cross Validation
Inference
Distributed Inference
Model storage
Indices and tables
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Index
Module Index
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Related Topics
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