This blog talks about handling imbalance in data for classification using different sampling methods.
Discussing the theory behind ANN and the math behind back-propagation.
First among the series of blogs on ANN. Implemented ‘AND-gate’ logic as an ANN from scratch.
Step by step explanation of CART decision tree classification using Titanic dataset.
Explaining the curse of dimensionality using a relevant example
Step by step explanation of CHAID decision trees using the Titanic data set
K means clustering explained using customer segmentation in R. Touches on Silhouette statistic, Calinski and Harabasz index and Elbow curve.
After a brief introduction to PCA and CFA, hypothesis tests like KMO,Bartlett’s test of sphericity are introduced. In PCA, Scree plot, eigenvalues, validation and interpreting the factors is discussed.