[MINOR] Generate Python tSNE builtin
diff --git a/src/main/python/systemds/operator/algorithm/builtin/tSNE.py b/src/main/python/systemds/operator/algorithm/builtin/tSNE.py index 3c65916..49eeee1 100644 --- a/src/main/python/systemds/operator/algorithm/builtin/tSNE.py +++ b/src/main/python/systemds/operator/algorithm/builtin/tSNE.py
@@ -35,6 +35,16 @@ This function performs dimensionality reduction using tSNE algorithm based on the paper: Visualizing Data using t-SNE, Maaten et. al. + There exists a variant of t-SNE, implemented in sklearn, that first reduces the + dimenisonality of the data using PCA to reduce noise and then applies t-SNE for + further dimensionality reduction. A script of this can be found in the tutorials + folder: scripts/tutorials/tsne/pca-tsne.dml + + For direct reference and tips on choosing the dimension for the PCA pre-processing, + you can visit: + https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/manifold/_t_sne.py + https://lvdmaaten.github.io/tsne/ + :param X: Data Matrix of shape @@ -44,9 +54,12 @@ :param lr: Learning rate :param momentum: Momentum Parameter :param max_iter: Number of iterations + :param tol: Tolerance for early stopping in gradient descent :param seed: The seed used for initial values. If set to -1 random seeds are selected. :param is_verbose: Print debug information + :param print_iter: Intervals of printing out the L1 norm values. Parameter not relevant if + is_verbose = FALSE. :return: Data Matrix of shape (number of data points, reduced_dims) """