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Learing to Rank Query w/ RankLib Models
/*
* Copyright [2017] Wikimedia Foundation
*
* Licensed 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 com.o19s.es.ltr.ranker;
import java.util.Arrays;
/**
* Simple array-backed feature vector
*/
public class DenseFeatureVector implements LtrRanker.FeatureVector {
public final float[] scores;
/**
* New simple array-backed datapoint
* @param size size of the internal array
*/
public DenseFeatureVector(int size) {
this.scores = new float[size];
}
@Override
public void setFeatureScore(int featureIdx, float score) {
scores[featureIdx] = score;
}
@Override
public float getFeatureScore(int featureIdx) {
return scores[featureIdx];
}
public void reset() {
Arrays.fill(scores, 0F);
}
}