References for Linear Classifiers

I take Machine Learning this semester. Linear model was covered recently, that is, linear regression and linear classification. In linear regression, a connection was established between least-squared-error and MLE under Gaussian assumption in errors. In linear classification, two models were introduced. In Generative model, conditional-independence was assumed and join probability was derived by applying Naive Bayes. In Discriminative model, a linear form was assumed, and posterior probability was derived by combining linear regression with logistic function. Here is the information which is helpful for learning the subject.

Sample chapter:

• Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression

Machine Learning Course Materials:

• Supervised Learning, Discriminative Algorithms
• Generative Algorithms
• Problem Set

Article:

• Gradient descent
• Logistic regression
• Linear discriminant analysis
  

Paper:

• On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes