// Copyright (C) 2010, 2011 Zeno Gantner, Chris Newell
//
// This file is part of MyMediaLite.
//
// MyMediaLite is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// MyMediaLite is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with MyMediaLite. If not, see <http://www.gnu.org/licenses/>.
package org.mymedialite.ratingprediction;
import org.mymedialite.correlation.Pearson;
import org.mymedialite.taxonomy.EntityType;
/**
* Weighted user-based kNN with Pearson correlation.
*
* This recommender supports incremental updates.
* @version 2.03
*/
public class UserKNNPearson extends UserKNN {
/**
* Shrinkage (regularization) parameter.
*/
public float shrinkage = 10;
/**
*
*/
public void train() {
baseline_predictor.train();
this.correlation = Pearson.create(ratings, EntityType.USER, shrinkage);
}
/**
*/
protected void retrainUser(int user_id) {
baseline_predictor.retrainUser(user_id);
if (updateUsers)
for (int i = 0; i <= maxUserID; i++)
correlation.set(user_id, i, Pearson.computeCorrelation(ratings, EntityType.USER, user_id, i, shrinkage));
}
public String toString() {
return "UserKNNPearson k=" + (k == Integer.MAX_VALUE ? "inf" : k) + " reg_u=" + getRegU() + " reg_i=" + getRegI();
}
}