[R] Obtaining predicted probabilities for Logistic regression

[Christofer Bogaso]

Many thanks.

May be I need to check my eyes before anything!!!

On Sat, Jul 13, 2024 at 6:46 PM Rui Barradas <ruipbarradas using sapo.pt> wrote:
>
> Às 12:13 de 13/07/2024, Christofer Bogaso escreveu:
> > Hi,
> >
> > I ran below code
> >
> > Dat = read.csv('https://raw.githubusercontent.com/sam16tyagi/Machine-Learning-techniques-in-python/master/logistic%20regression%20dataset-Social_Network_Ads.csv')
> > head(Dat)
> > Model = glm(Purchased ~ Gender, data = Dat, family = binomial())
> > head(predict(Model, type="response"))
> > My_Predict = 1/(1+exp(-1 * (as.vector(coef(Model))[1] *
> > as.vector(coef(Model))[2] * ifelse(Dat['Gender'] == "Male", 1, 0))))
> > head(My_Predict)
> >
> > However, My_Predict and predict(Model, type="response")) are differing
> > when I tried to manually calculate prediction.
> >
> > Could you please help to identify what was the mistake I made?
> >
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> > and provide commented, minimal, self-contained, reproducible code.
> Hello,
>
> Sometimes when there is an error, the best way to correct it is to
> rewrite the offending part of the code.
> In your case, after as.vector(coef(Model))[1] you should have a plus sign.
>
>
>
> Dat =
> read.csv('https://raw.githubusercontent.com/sam16tyagi/Machine-Learning-techniques-in-python/master/logistic%20regression%20dataset-Social_Network_Ads.csv')
> head(Dat)
> Model = glm(Purchased ~ Gender, data = Dat, family = binomial())
>
> # use matrix algebra
> x <- cbind(1, (Dat$Gender == "Male")) %*% coef(Model)
> pred1 <- exp(x)/(1 + exp(x))
>
> # use the fitted line equation
> y <- coef(Model)[1L] + coef(Model)[2L] * (Dat$Gender == "Male")
> pred2 <- exp(y)/(1 + exp(y))
>
> head(predict(Model, type="response"))
> head(pred1) |> c()
> head(pred2)
>
>
> Hope this helps,
>
> Rui Barradas
>
>
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