Baunsgaard commented on a change in pull request #1124: URL: https://github.com/apache/systemds/pull/1124#discussion_r543245864
########## File path: scripts/builtin/pcaPredict.dml ########## @@ -0,0 +1,49 @@ +#------------------------------------------------------------- +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +# +#------------------------------------------------------------- + +# Principal Component Analysis (PCA) for dimensionality reduction prediciton +# +# This method is used to predict on data, which the PCA was not trained on. To validate how good +# The PCA is, and to apply in production. +# +# --------------------------------------------------------------------------------------------- +# NAME TYPE DEFAULT MEANING +# --------------------------------------------------------------------------------------------- +# X Matrix --- Input feature matrix +# Centering Matrix empty matrix The column means of the PCA model, subtracted to construct the PCA +# ScaleFactor Matrix empty matrix The scaling of each dimension in the PCA model +# --------------------------------------------------------------------------------------------- +# Y Matrix --- Output feature matrix dimensionally reduced by PCA +# --------------------------------------------------------------------------------------------- + +m_pcaPredict = function(Matrix[Double] X, Matrix[Double] Clusters, Matrix[Double] Centering, Matrix[Double] ScaleFactor) Review comment: sure transform works as well! :+1: ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
