Visual Representation of scikit-learn models#
sklearn-onnx converts many models from scikit-learn into ONNX. Every of them is a graph made of ONNX mathematical functions (see Python Runtime for ONNX operators, ONNX Operators, ONNX ML Operators). The following sections display a visual representation of each converted model. Every graph represents one ONNX graphs obtained after a model is fitted. The structure may change is the model is trained again.
- calibration
- cluster
- compose
- covariance
- cross_decomposition
- decomposition
- discriminant_analysis
- ensemble
- feature_extraction
- feature_selection
- gaussian_process
- impute
- isotonic
- kernel_approximation
- kernel_ridge
- linear_model
- mixture
- mlprodict.onnx_conv
- model_selection
- multiclass
- multioutput
- naive_bayes
- neighbors
- neural_network
- preprocessing
- random_projection
- semi_supervised
- svm
- tree