ricardocarvalhods

import numpy as np
from numpy import random
from sklearn import base

class PUWrapper(object):
    def __init__(self,trad_clf,n_fold=5):
        self._trad_clf=trad_clf
        self._n_fold=n_fold

    def fit(self,X,s):

ricardocarvalhods

makeglm <- function(formula, ..., family, data=NULL) {
    dots <- list(...)
    out<-list()
    tt <- terms(formula, data=data)
    if(!is.null(data)) {
        mf <- model.frame(tt, data)
        vn <- sapply(attr(tt, "variables")[-1], deparse)
 
        if((yvar <- attr(tt, "response"))>0)
            vn <- vn[-yvar]