This chapter is a continuation of the discussions and demonstrations of basic ML data models that started in the previous chapter. I presented ten data models at the beginning of the previous chapter, and these were
Linear regression
Logistic regression
K-nearest neighbors classifier
Gaussian Naive Bayesian
Decision tree classifier
Principal component analysis
Linear discriminant analysis
Support vector machines
Learning vector quantization
Bagging and random forests
The first five was covered in the previous chapter, while the remaining five will be covered in ...
