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I use Package ‘monmlp’ package in R as follows. (Monotone multi-layer perceptron neural network)

model = monmlp.fit(trainData, trainLabs, hidden1=3, n.ensemble=1, bag=F,silent=T) 
pred = monmlp.predict(testData,model)

preds = as.numeric(pred)
labs = as.numeric(testLabs)

pr = prediction(preds,labs)
pf = performance(pr,"auc")

I want to predict some new data using the trained model and take the instances which result higher than a threshold value like 0.9. In brief, I want to take instances that more likely to be in class 1 using a threshold.

classes are 0 and 1, and

pred = monmlp.predict(testData,model)


311694 0.005271582
129347 0.005271582
15637  0.005271582
125458 0.005271582
315130 0.010411831
272375 0.010411831

What are these values? Probabilty values? If yes what does these values mean?

[1] 1023.839 1023.839 1023.839


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Regarding the output: "a matrix with number of rows equal to the number of samples and number of columns equal to the number of predictand variables. If weights is from an ensemble of models, the matrix is the ensemble mean and the attribute ensemble contains a list with predictions for each ensemble member."

Source: http://cran.r-project.org/web/packages/monmlp/monmlp.pdf

I've never used the package nor the technique, but maybe the quoted answer may mean something to you

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I have seen this comment. It only explains what the rows and columns are. Still I don't know what are the values :/ Thanks. –  ykpemre Jul 3 '13 at 14:01
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