您不需要hadoop at所有嘗試mahout。下面是一個示例代碼,它將模型作爲文件的輸入並將打印推薦。
package com.ml.recommend;
import java.io.File;
import java.io.IOException;
import java.util.List;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
import org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood;
import org.apache.mahout.cf.taste.impl.recommender.CachingRecommender;
import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import org.apache.mahout.cf.taste.recommender.Recommender;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;
public class App {
public static void main(String[] args) throws IOException, TasteException {
DataModel model = new FileDataModel(new File("data.txt"));
UserSimilarity userSimilarity = new PearsonCorrelationSimilarity(model);
UserNeighborhood neighborhood = new NearestNUserNeighborhood(3,
userSimilarity, model);
Recommender recommender = new GenericUserBasedRecommender(model,
neighborhood, userSimilarity);
Recommender cachingRecommender = new CachingRecommender(recommender);
List<RecommendedItem> recommendations = cachingRecommender.recommend(
1000000000000006075L, 10);
System.out.println(recommendations);
}
}
爲什麼不試試看?你說「不是全部」取決於Hadoop,但其他人怎麼知道你是否需要這些部件呢? – millimoose
我只想弄清楚爲什麼Hadoop安裝Mahout或者不需要安裝Mahout。現在,我正在嘗試首先安裝Hadoop,以防發生不良情況。 –
可能的重複[是否可以使用沒有hadoop依賴的Apache mahout?](http://stackoverflow.com/questions/7815317/is-it-possible-to-use-apache-mahout-without-hadoop-dependency) – millimoose