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Simplified example program.

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This commit is contained in:
Davis King 2014-04-05 16:56:48 -04:00
parent f1aecac5ac
commit 137b7f80c8
1 changed files with 5 additions and 7 deletions
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12
examples/assignment_learning_ex.cpp
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@ -116,7 +116,7 @@ struct feature_extractor
unsigned long num_features() const
{
// Return the dimensionality of feature vectors produced by get_features()
return num_dims + 1;
return num_dims;
}
void get_features (
@ -132,12 +132,10 @@ struct feature_extractor
is "good").
!*/
{
// We will have:
// - feats(i) == std::pow(left(i) - right(i), 2.0)
// Except for the last element of feats which will be equal to 1 and
// therefore function as a bias term. Again, how you define this feature
// extractor is highly problem dependent.
feats = join_cols(squared(left - right), ones_matrix<double>(1,1));
// Lets just use the squared difference between each vector as our features.
// However, it should be emphasized that how to compute the features here is very
// problem dependent.
feats = squared(left - right);
}
};