Revision: 17312
http://sourceforge.net/p/gate/code/17312
Author: valyt
Date: 2014-02-15 12:59:04 +0000 (Sat, 15 Feb 2014)
Log Message:
-----------
Slightly better comment for whoever gets lost in these parts in the future.
Modified Paths:
--------------
gate/trunk/plugins/Text_Categorization/src/gate/ml/categorization/TextCategorizationPR.java
Modified:
gate/trunk/plugins/Text_Categorization/src/gate/ml/categorization/TextCategorizationPR.java
===================================================================
---
gate/trunk/plugins/Text_Categorization/src/gate/ml/categorization/TextCategorizationPR.java
2014-02-14 18:49:50 UTC (rev 17311)
+++
gate/trunk/plugins/Text_Categorization/src/gate/ml/categorization/TextCategorizationPR.java
2014-02-15 12:59:04 UTC (rev 17312)
@@ -397,13 +397,17 @@
double probability = 1.0;
// do we need to check probabilities?
if(categoryThresholds != null && categoryThresholds[label] > 0) {
- // prob[i] is the value of $\theta_T x$
+ // prob[i] is the value of $\theta^T x$
// Once mapped through the logistic function, this becomes the
// probability of the instance belonging to class i, as opposed to
// all other classes.
- // LIBLINEAR would normalize this so that all probs sum up to 1,
- // but we don't want that, as we're only interested in the confidence
- // the model has in this particular classification.
+ // LIBLINEAR normalizes the values so that all probabilities sum up
+ // to 1 (i.e. the output is a probability distribution over the set
+ // of classes). They should really be using softmax for that, but
+ // anyway...
+ // However, we don't want that, as we're only interested in the
+ // confidence the model has in this particular classification, and
we
+ // don't know for sure that the classes are mutually-exclusive
probability = probs[label];
// convert to an actual probability, by applying the logistic
function
probability = 1 / (1 + Math.exp(-probability));
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