It depends which classification algorithm you are using, but the
simplest way to do this with classifiers that output a score would be to
change the threshold. If the classification algorithm you want to use
doesn't have any sort of confidence measure then the best thing for you
to do would be to search Google as I think it's a pretty open
question... you might be able to bias the training set in one direction
or another, for example, but this has drawbacks.
With the threshold method - you can do it manually (by looking at the
scores output for each item in a test set) or automatically, using the
i.e. in Weka explorer, load in your training data then go to the
Classify tab. Select Meta -> ThresholdSelector in the "Classifier"
panel. Click on the text box next to the "Choose" button to select which
classifier you want to use and which class you're most interested in
then go ahead and click Start. See the ThresholdSelector help text for
Hope that helps,
In weka, How can give more weight to precision of class in classification? It
need not recall all the instances!