The dataset is a full ranked binary dataset. Therefore,
Y = 1 or 0and
X's = 1 or 0. Y represents whether a car has an engine failure or not.
X represents the features of the car, for example
X1 is engine type A,
X2 engine type B,
X3 gear type etc. I want to know from your experience, which models work well on those type of datasets. I read somewhere, that
KNNare not recommended, as well as
Which information criterion would you use for forward selection?
The data looks like this
Engine_A Engine_B Engine_C Color_R Color_B Color_G Y_Failure Car1 1 0 0 0 1 0 1 Car2 0 1 0 1 0 0 0 Car3 0 1 0 0 0 1 1
Would you factorize all variables X and Y?