| #------------------------------------------------------------- |
| # |
| # 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. |
| # |
| #------------------------------------------------------------- |
| |
| # Imports |
| source("staging/fm-regression.dml") as fm_regression |
| |
| # generate dummy data (just a sample!) |
| n = 1000; d = 9; k=2; |
| X = rand(rows=n, cols=d); |
| y = rand(rows=n, cols=1); |
| X_val = rand(rows=100, cols=d); |
| y_val = rand(rows=100, cols=1); |
| |
| # Train |
| [w0, W, V] = fm_regression::train(X, y, X_val, y_val); |
| |
| # Write model out |
| #write(w0, out_dir+"/w0"); |
| #write(W, out_dir+"/W"); |
| #write(V, out_dir+"/V"); |
| |
| # Evaluate |
| probs = fm_regression::predict(X, w0, W, V); |
| [loss, accuracy] = fm_regression::eval(probs, y); |
| |
| # Output results |
| print("Test Accuracy: " + accuracy) |
| #write(accuracy, out_dir+"/accuracy") |
| |
| print("") |