What does logp output in classify exactly mean?

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Maria 2014-4-28

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评论： Maria 2014-5-6

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!

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the cyclist 2014-4-28

My expectation is the same as yours, Maria, but I am not an expert on this. My guess is that you are hitting some numerical instability. Are you able to post the smallest possible self-contained example that will exhibit the phenomenon?

Maria 2014-4-28

在 MATLAB Online 中打开

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!

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Answer 1

Ilya 2014-4-30

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https://ww2.mathworks.cn/matlabcentral/answers/127518-what-does-logp-output-in-classify-exactly-mean#answer_135197

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.

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Ilya 2014-5-5

classify returns a vector of logp values, just as the doc says. You get one value because you pass one query point in. Take as many query points as you'd like, concatenate them in a matrix and pass them as the first input to classify. Form query points to sample the space with whatever granularity you choose.

Maria 2014-5-6