Hi,
I am trying to do some classification with Mahout's
OnlineLogisticRegression, I've built a model and have it trained on 5
categories of interest to me. I however was under the impression that the
classify() and classifyFull() methods would return a vector of floats that
totaled to 1.0 .. However I get a vector back and it only has a 1 in the
index position of the category that it thinks it's supposed to be in. Is
this the normal behavior? I have about 500 training items for each
category. I've played with the value of lambda some but it doesn't change.
If this is the intended outcome, could someone point me to a way to provide
a confidence value for items that I classify, or should I be looking at a
recommender?
My goal is to have some sort of confidence score to indicate the level of
certainty that this is what it says it is, as well as put the exemplar data
into a category.
I am trying to do some classification with Mahout's
OnlineLogisticRegression, I've built a model and have it trained on 5
categories of interest to me. I however was under the impression that the
classify() and classifyFull() methods would return a vector of floats that
totaled to 1.0 .. However I get a vector back and it only has a 1 in the
index position of the category that it thinks it's supposed to be in. Is
this the normal behavior? I have about 500 training items for each
category. I've played with the value of lambda some but it doesn't change.
If this is the intended outcome, could someone point me to a way to provide
a confidence value for items that I classify, or should I be looking at a
recommender?
My goal is to have some sort of confidence score to indicate the level of
certainty that this is what it says it is, as well as put the exemplar data
into a category.