Compare Two Vectors (Java)
Currently I have two larger vectors of 50+ strings
I want to be able to compare these two Vectors and work out how similar they are. I think I need to use Cosine similarity?
Does anyone know of any methods that take in two Java Vectors and giv开发者_JS百科es a value between 0 and 1 as to how similar they are?
Thanks Phil
Have a look at the similarity function in Lucene.
the above formula is motivated by the cosine-distance or dot-product between document and query vector
Here's a Previous SO question on this topic.
See the Apache Mahout library for implementations of Cosine Distance and related approaches. Also consider looking up Locality Sensitive Hashing for a much speedier alternative.
Do the following
package com.example;
import java.util.Collection;
import java.util.HashMap;
import java.util.Map;
/** Computes the similarity between two bags of words.
* 1.0 is most similar, 0.0 is most unsimilar.
*
*/
public class Cosine {
public static double cosine(Collection<String> a, Collection<String> b) {
Map<String,Integer> aa = asBag(a);
Map<String,Integer> bb = asBag(b);
double sum = 0;
for (String word: aa.keySet()) {
if (!bb.containsKey(word)) continue;
sum += aa.get(word) * bb.get(word);
}
return sum / (norm(aa) * norm(bb));
}
private static double norm(Map<String, Integer> bag) {
double sum = 0;
for (int each: bag.values()) sum += each * each;
return Math.sqrt(sum);
}
private static Map<String,Integer> asBag(Collection<String> vector) {
Map<String,Integer> bag = new HashMap<String,Integer>();
for (String word: vector) {
if (!bag.containsKey(word)) bag.put(word,0);
bag.put(word, bag.get(word) + 1);
}
return bag;
}
}
Type inference, anyone?
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