[R] Practical work with logistic regression

[Gabor Grothendieck]

confusionMatrix in the caret package can be used to replace your
manual procedure.

You could try using RWeka, the R interface to the java Weka software.
Once you have it working you could then directly interface your java
program to Weka without involving R.

On Thu, Apr 22, 2010 at 9:29 PM, Claus O'Rourke <claus.orourke at gmail.com> wrote:
> Dear all,
>
> I have a couple of short noob questions for whoever can take them. I'm
> from a very non-stats background so sorry for offending anybody with
> stupid questions ! :-)
>
> I have been using logistic regression care of glm to analyse a binary
> dependent variable against a couple of independent variables. All has
> gone well so far. In my work I have to compare the accuracy of
> analysis to a C4.5 machine learning approach. With the machine
> learning, a straight-forward measure of the quality of the classifier
> is simply the percentage of correctly classified instances. I can
> calculate this for the resultant model by comparing predictions to
> original values 'manually'. My question: is this not automatically -
> or easily - calculated in the produced model or the summary of that
> model?
>
> I want to use my model in real time to produce results for new inputs.
> Basically this model is to be used as a classifier for a robot in real
> time. Can anyone suggest the best way that a produced model can be
> used directly in external code once the model has been developed in R?
> If my external code is in Java, then using jri is one option. A more
> efficient method would be to take the intercept and coefficients and
> actually code up the function in the appropriate programming language.
> Has anyone ever tried doing this?
>
> Apologies again for the stupid questions, but the sooner I get some of
> these things straight, the better.
>
> Claus