No regular here will be unaware of the perils of using stepwise and similar automatic methods for variable selection in regression analysis. But preferred alternatives, such as the lasso or ...
Stepwise Regression works as follows if I'm correct: fit the initial model add the variable which has its f-stat larger than a in-threshold and repeat step 2. if there are no candidates to enter - ...
My client wants me to implement Variable selection methods i.e. Forward, Backward, Step and LASSO in VB .Net platform including p-value and AIC. I have no idea about the steps involved to calculate ...
I have two data sets from different collections. The second data set is smaller. They were both analyzed with the same methods in order to derive feature sets of 10-30 features each. Each feature set ...
I am trying to perform stepwise regression for variable selection in R. In matlab, the stepwisefit function is able to work in ...
The (training) data contains 1280 observations with 1415 features. The test set has additional 380 observations. The data is sparse, that is, many of the variables has many zeros and few positive ...
In a dataset of two non-overlapping populations (patients & healthy, total $n=60$) I would like to find (out of $300$ independent variables) significant predictors for a continuous dependent ...
I have a data set with about 70 variables that I'd like to cut down. What I'm looking to do is use CV to find most useful variables in the following fashion. 1) Randomly select say 20 variables. ...