mob-ai commented on a change in pull request #26124: [SPARK-29224][ML]Implement Factorization Machines as a ml-pipeline component URL: https://github.com/apache/spark/pull/26124#discussion_r342371780
########## File path: mllib/src/test/scala/org/apache/spark/ml/classification/FMClassifierSuite.scala ########## @@ -0,0 +1,143 @@ +/* + * 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. + */ + +package org.apache.spark.ml.classification + +import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput +import org.apache.spark.ml.linalg.{DenseVector, Vector, Vectors} +import org.apache.spark.ml.param.ParamsSuite +import org.apache.spark.ml.regression.FMRegressorSuite._ +import org.apache.spark.ml.util._ +import org.apache.spark.ml.util.TestingUtils._ +import org.apache.spark.sql.{DataFrame, Row} + +class FMClassifierSuite extends MLTest with DefaultReadWriteTest { Review comment: I want to compare with libFM, but randomly generate a binary dataset, FM can't fit the dataset perfectly. Generally, I get very small loss value, but the parameters are not exactly same every time (also in libFM). My current test method is that for mse to generate a feature-interaction dataset, FMRegressor needs to fit this dataset perfectly, bias/linearVector needs same, every `<v_i, v_j>` needs same that calculates by factorMatrix. However, for FMClassifier, it is difficult to generate a binary feature-interaction dataset, so for the FMClassifier, I don't verify the correctness of interaction logic (that is verify in mse), only verify the correctness of logloss logic. ---------------------------------------------------------------- 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: [email protected] With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
