Following are various Machine Learning information sources to review:
- Comparison of algorithms for choosing based on a given dataset
Tammi donated these links:
- Hastie and Tibshirani’s Free Stanford Statistical learning course
- These are the text books (all free of charge and classics)
Following are additional notes on the various algorithms.
Support Vector Machines
These are Eric Johnson’s notes from his machine learning course on SVMs:http://focusnumeric.net/PDFs/Stanford%20ML%20-%20Week%207%20Lecture%20Notes.pdf
Note that both Naive Bayesian and Logistic Regression compute p(label|feature), but Naive Bayesian computes it via p(feature|label) and Logistic Regression computes it directly.
Following are some useful links on the Logistic Regression algorithm: