search for: phiberoptic_br

Hello R-USERS, I think some people didn't understand my question. What I want is to use the training set to minimize the FALSE POSITIVE RATE. I think it is possible. I sacrifice ACCURACY to have less FALSE POSITIVES. I don't want a classifier result with 5% of FPR and, for example, 93% of ACCURACY. I want a 1% FPR sacrificing the 93% ACCURACY. Do you know how can I do this? I really

Dears, I saw in the R-project site some R-books. However, I'm new in this community and I didn't figure out what are the best books. Can you suggest me some "reference" books? My intentions with R is concerned to Artificial Intelligence simulations, Classification and general Statistics (e.g., regression, multivariate regression, etc). Thanks for any help, Anderson

Dear R-users, Does anyone know how to get margins' information using SVM under package e1071? I have a two class classification problem and I'd like to have, for each input example, the distance of this example to the margin just like it's possible to obtain using C-based SVM-light, for instance. Thanks in advance, -- Anderson

Dear R-users, I have a set of 12000 image samples. I can divide this set into two categories: training and testing. I need to classify the test set into a two qualitative outputs: true or false for some characteristic. To do the classification I'm using the packages SVM in e1071 library and LDA in the MASS library. However, I'm with a great number of FALSE POSITIVE CASES in both