Perhaps I already have it, but I simply do not know how to make sense of trained model results in R to make useful predictions out of R on new data. I just don't have statistics background, but I have programming background.
So I think I just need someone who knows enough statistics and enough about R to show me how to make sense of training results in my R script.
I need the attached R script modified to accomplish the following:
*(1)* Extract the result/formula, (formula values) of the classification models for each group/class, (-2,0,2) after my attached R script completes Stepwise LDA, QDA and Logistic Regression. I want formula values, not the formula code so I can make predictions out of R on new data.
*(2)* Extract the formula for the decision bounds that separates the groups/classes, (-2,0,2) after my attached R script completes Stepwise LDA, QDA and Logistic Regression. I want formula decision bounds, not the decision bounds code so I can make predictions out of R on new data.
Specifically, I want my R script, (see attached .zip in job posting) modified to give me the data necessary to do similar to what is seen in video in [Column D] and in [Cells F21:G25] and [Column E], but for after I run my R script for LDA, QDA and Logistic Regression.
-- See video from *2:18 to 4:05* for [Column D]
-- See video from *4:05 to 7:31* for [Cells F21:G25]
-- See video from *7:32 to 8:28* for [Column E]
This screenshot might be a good example of the values I need extracted from LDA, QDA and Logistic Regression in R http://www.screencast.com/t/hmUHHvrRF7cV