| /** |
| * 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.horn.core; |
| |
| import java.util.Arrays; |
| import java.util.List; |
| |
| /** |
| * The common methods for testing machine learning algorithms |
| * |
| */ |
| public abstract class MLTestBase { |
| |
| /** |
| * Conduct the 0-1 normalization. |
| * |
| * @param instances |
| */ |
| protected static void zeroOneNormalization(List<double[]> instanceList, |
| int len) { |
| int dimension = len; |
| |
| double[] mins = new double[dimension]; |
| double[] maxs = new double[dimension]; |
| Arrays.fill(mins, Double.MAX_VALUE); |
| Arrays.fill(maxs, Double.MIN_VALUE); |
| |
| for (double[] instance : instanceList) { |
| for (int i = 0; i < len; ++i) { |
| if (mins[i] > instance[i]) { |
| mins[i] = instance[i]; |
| } |
| if (maxs[i] < instance[i]) { |
| maxs[i] = instance[i]; |
| } |
| } |
| } |
| |
| for (double[] instance : instanceList) { |
| for (int i = 0; i < len; ++i) { |
| double range = maxs[i] - mins[i]; |
| if (range != 0) { |
| instance[i] = (instance[i] - mins[i]) / range; |
| } |
| } |
| } |
| |
| } |
| } |