#' Generates an equation
#'
#' Generates an equation of the form Y = a + bX, where X is the explanatory variables and Y is the dependent variable. Using this equation we can find the probability of being the dependent variable.
#'
#' @param dataSource the data frame to process.
#' @param model the GLM model where to extract the coefficients from.
#' @return text
#' @export
generateEquation <- function(dataSource, model){
equation <- (gsub(paste("\\*\\s", deparse(substitute(dataSource)), "\\$\\(Intercept\\)\\s\\+", sep=""), "- (", (paste(coef(model), names(coef(model)), sep = paste(' * ',gsub(" ", "", deparse(substitute(dataSource))),'$', sep=""), collapse = ' + '))))
evEquation <- paste("1/(1+exp((-", equation, "))))", sep = "")
loginfo(paste("Number of Metrics Used to Generate the Estaimate Probability Equation", nchar(gsub("[^*]","",evEquation)), sep = " : "), logger="motsai.equation")
return(evEquation)
}
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