blob: 77969184a1d26a71b5c01520d8eb753a00ecb683 [file] [log] [blame]
#-------------------------------------------------------------
#
# 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("")