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#' How would it be if we were naive ?
#' @description Describe the result of a naive binary discriminant model
#' @param proba_1 The ratio of 1 in the population (if nb_1 is NULL)
#' @param effectif The global effective of the population
#' @param nb_1 The number of 1 in the population.If not NULL proba_1 is not read.default=NULL
#' @export
naive_model<-function(proba_1=0.8,effectif=100,nb_1=NULL){
if(!is.null(nb_1)){
vrai=rep(0,times=effectif)
vrai[1:nb_1]=1
proba_1=nb_1/effectif
}else{
vrai=runif(n = effectif,min=0,max=1)
vrai[vrai>proba_1]=0
vrai[vrai!=0]=1
}
pred=runif(n = effectif,min=0,max=1)
pred[pred>proba_1]=0
pred[pred!=0]=1
count=table(pred,vrai)
percent=count/effectif
balance=data.frame(percent[1,1]+percent[2,2],percent[1,2]+percent[2,2]);names(balance)=c("TRUE","FALSE")
return(list(count=count,percent=percent,balance=balance))
}
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