edu.uci.jforestsx.learning.bagging.BaggingConfig Maven / Gradle / Ivy
/**
* 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 edu.uci.jforestsx.learning.bagging;
import java.util.Map.Entry;
import edu.uci.jforestsx.config.ComponentConfig;
import edu.uci.jforestsx.util.ConfigHolder;
/**
* @author Yasser Ganjisaffar
*/
public class BaggingConfig extends ComponentConfig {
/**
* Number of bags
*/
public int bagCount = 10;
private final static String BAG_COUNT = "bagging.bag-count";
/**
* Fraction of training instances that should be randomly selected
* for training of each bag.
*/
public double trainFraction = 0.67;
private final static String TRAIN_FRACTION = "bagging.train-fraction";
/**
* Should we perform backfitting during the bagging process?
*/
public boolean backfitting = false;
private final static String BACKFITTING = "bagging.backfitting";
public void init(ConfigHolder config) {
for (Entry entry : config.getEntries()) {
String key = ((String) entry.getKey()).toLowerCase();
String value = (String) entry.getValue();
if (key.equals(BAG_COUNT)) {
bagCount = Integer.parseInt(value);
} else if (key.equals(TRAIN_FRACTION)) {
trainFraction = Double.parseDouble(value);
} else if (key.equals(BACKFITTING)) {
backfitting = Boolean.parseBoolean(value);
}
}
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append(BAG_COUNT + ": " + bagCount + "\n");
sb.append(TRAIN_FRACTION + ": " + trainFraction + "\n");
sb.append(BACKFITTING + ": " + backfitting);
return sb.toString();
}
}