Do we need normo normalize SimilarityMatrixEntryKey?
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Key: MAHOUT-478
URL: https://issues.apache.org/jira/browse/MAHOUT-478
Project: Mahout
Issue Type: Question
Components: Collaborative Filtering
Affects Versions: 0.4
Reporter: Han Hui Wen
Fix For: 0.4
In org.apache.mahout.math.hadoop.similarity.SimilarityMatrixEntryKey
{code}
public static class SimilarityMatrixEntryKeyComparator extends
WritableComparator {
protected SimilarityMatrixEntryKeyComparator() {
super(SimilarityMatrixEntryKey.class, true);
}
@Override
public int compare(WritableComparable a, WritableComparable b) {
SimilarityMatrixEntryKey key1 = (SimilarityMatrixEntryKey) a;
SimilarityMatrixEntryKey key2 = (SimilarityMatrixEntryKey) b;
int result = compare(key1.row, key2.row);
if (result == 0) {
result = -1 * compare(key1.value, key2.value);
}
return result;
}
protected static int compare(long a, long b) {
return (a == b) ? 0 : (a < b) ? -1 : 1;
}
protected static int compare(double a, double b) {
return (a == b) ? 0 : (a < b) ? -1 : 1;
}
}
{code}
We used double as one part of the key,
because of double has many possible value ,it will cause pairwiseSimilarity may
has may group,
for example (ItemA ,0.1),(ItemA ,0.11),(ItemA ,0.01),(ItemA ,0.1),(ItemA
,0.001),(ItemA ,0.0011) is different group.
Also double is inaccurate,it hard to compare the equal of double .
So can we normalize the similarityValue ?
multiply all similarityValue with 100,1000 ,or other numer,and make it to a
integer.
If necessary we can transform them to double in the end.
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