I have a response variable with 2 categories and $500$ predictor variables. The $500$ coefficient $a_1, a_2, a_3, \ldots, a_{500}$ ranges $(-1, 1)$. Positive $a_i$ indicates category A; negative $a_i$ indicates category B. The larger the coefficient, the stronger it indicates its correspondent category. I get the coefficient from a researcher, who score each coefficient from -1 to 1 based on the importance and influence in classification.
To classify an object that have attributes $x_1, x_2, x_3,\ldots,x_{500}$, I am thinking of using logistic regression. But I do not know how to deal with continuous data (the range of the coefficient is continuous from -1 to 1). Is logistic regression viable?
If not, will someone help with other methods and post your code? I prefer using R.
