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Study Note: Linear Discriminant Analysis, ROC & AUC, Confusion Matrix

LDA V.S. Logistic Regression: When the classes are well-separated, the parameter estimates for the logistic regression model are surprisingly unstable. Linear discriminant analysis does not suffer from this problem. If n is small and the distribution of the predictors X is approximately normal in each of the classes, the linear discriminant model is again more stable than the logistic regression model. Linear discriminant analysis is popular when we have more than two response classes. ...

Study Note: Bias, Variance and Model Complexity

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Study Note: Logistic Regression

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Study Note: Linear Regression Part II - Potential Problems

Qualitative Predictors Predictors with Only Two Levels Suppose that we wish to investigate differences in credit card balance between males and females, ignoring the other variables for the moment. If a qualitative predictor (also known as a factor) only has two levels, or possible values, then incorporating it into a regression model is very simple. We simply create an indicator or dummy variable that takes on two possible numerical values. and use this variable as a predictor in the regression equation. This results in the model ...

Apache Spark: Advanced Topics

Study note of Big Data Essentials: HDFS, MapReduce and Spark RDD ...