# What does logp output in classify exactly mean?

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Maria on 28 Apr 2014
Commented: Maria on 6 May 2014
Hi all!
I am using the classify function but I obtain positive values in the logp output parameter. If I understand correctly this is the logarithm of a probability and consequently should't be larger than 0. Is that correct? If so, what could cause getting these values?
Thank you very much!
Maria on 28 Apr 2014
Let's say that our query is:
query = [-0.6824 -0.0764 -0.4608 -0.0770 -0.5227]
Our training data is: train_x =
[-0.6837 -0.0789 -0.5838 -0.0436 -0.6582;
-0.5692 -0.0707 -0.5459 -0.0083 -0.5791;
-0.6475 -0.0597 -0.6075 -0.1157 -0.6768;
-0.7199 -0.0655 -0.5886 -0.1927 -0.6442;
-0.8650 -0.0616 -0.3579 -0.0563 -0.4931;
-0.7285 -0.0545 -0.2680 -0.1328 -0.3348;
-0.7717 -0.0749 -0.6171 -0.1440 -0.7033;
-0.4889 -0.0675 -0.5421 -0.1596 -0.5656;
-0.5019 -0.0822 -0.5932 -0.1313 -0.6452;
-0.5383 -0.0781 -0.6051 0.0638 -0.6635;
-0.8107 -0.0592 -0.5815 -0.2463 -0.6475;
-0.8576 -0.0607 -0.5961 -0.1486 -0.6813;
-0.8214 -0.0753 -0.6193 0.0215 -0.7097;
-0.7035 -0.0489 -0.4232 0.1721 -0.4677;
-0.8102 -0.0533 -0.2051 -0.2215 -0.3409]
and the labels : y = [-1; -1 ; -1; 1; -1; -1; -1; -1; 1; -1; -1; -1; -1; -1; -1]
Then if we do: [pred_query_fisher, train_err, pos_query, logp] = classify(query, train_x, train_y)
logp will be 7.2821
Thanks!

Ilya on 30 Apr 2014
Quoting from the doc for classify:
[class,err,POSTERIOR,logp] = classify(...) also returns a vector logp containing estimates of the logarithms of the unconditional predictive probability density of the sample observations...
Values of probability density do not need to be less than one.
Maria on 6 May 2014
I just want to classify one query at a time. I guess this output is useless in my case. Thanks

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