yobx.sklearn.decomposition.truncated_svd#
- yobx.sklearn.decomposition.truncated_svd.sklearn_truncated_svd(g: GraphBuilderExtendedProtocol, sts: Dict, outputs: List[str], estimator: TruncatedSVD, X: str, name: str = 'truncated_svd') str[source]#
Converts a
sklearn.decomposition.TruncatedSVDinto ONNX.Unlike PCA, TruncatedSVD does not center the data before projecting. The transformation is simply a matrix multiplication:
X ──MatMul(components_.T)──► output
- Parameters:
g – the graph builder to add nodes to
sts – shapes defined by scikit-learn
estimator – a fitted
TruncatedSVDoutputs – desired output names (projected inputs)
X – input tensor name
name – prefix name for the added nodes
- Returns:
output tensor name