Hi,
I am using random forest of Mahout. It works well when I don't use feature
descriptor with Ignore feature ( No I flag).
If using Ignore flag, the returned feature value is -1
(for in the code dataset.valueOf(aId, token) return -1).
I did some investigation, and found that there some problems in the
DataConverter.java
source code
------
for (int attr = 0; attr < nball; attr++) { --51
if (ArrayUtils.contains(dataset.getIgnored(), attr)) {
continue; // IGNORED
}
String token = tokens[attr].trim();
if ("?".equals(token)) {
// missing value
return null;
}
if (dataset.isNumerical(aId)) { --63
vector.set(aId++, Double.parseDouble(token));
} else { // CATEGORICAL
vector.set(aId, dataset.valueOf(aId, token)); --66
aId++;
}
-------
Let feature descriptor be 9 I N L (Breiman Example)
11 features, 1-9 Ignored, 10th is Numeric, 11th is label variable
(Is Breiman example really works based on web instruction ?)
line 51 -- attr is #feature, 0-10
aId is filtered feature #, 0-1 ( two non-Ignored features)
Problem in line 66
if attr=10, Label feature
aId=1
token=true
dataset.valueOf(aId, token) return -1 , for current code, CATEGORICAL
feature valueOf() kind mixed aId and attr concept.
Just by changing line 66
vector.set(aId, dataset.valueOf(aId, token)); --66
to vector.set(aId, dataset.valueOf(attr, token));
not working, because some validation fails (also attr, aId mixture).
There might be things that I overlook, just some thoughts.
Sam
