Logistic regression 1: Model and loss

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  1. Herman Kamper
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Nice job Herman carry on with the videos. May I ask which statistical book you would recommend regarding statistical modelling?
I am looking for in depth analysis on the models including anova tables on coefficients, proof on normality assumptions on error terms for linear regression and so on with actual proofs as well ways to approach comparing different models and choosing an optimal one. Also is this paint where you write or some other program?

I am studying machine learning and deep learning at the moment and I noticed that in many cases of regression models for example they just test the accuracy of a model and never bother constructing anova tables and malus cp. They also seem to completely ignore the accuracy on the training set.

panagiotisgoulas
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great explanation! Do you know if the bias term is included by default in python's sklearn logistic regression libraries?

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