Page 29 - E-catelog for advanced Course (2)

 Lift charts and Gain charts

 Regularization Techniques

 Lasso and Ridge Regressions

 Logit and Log Likelihood

 Category Baselining

 Modeling Nominal categorical data

 Data Mining Unsupervised - Clustering

 Hierarchial

 Supervised vs Unsupervised learning

 Data Mining Process

 Measure of distance

 Numeric - Euclidean, Manhattan, Mahalanobis

 Categorical - Binary Euclidean, Simple Matching Coefficient,

Jaquard’s Coefficient

 Types of Linkages

 Single Linkage / Nearest Neighbour

 Complete Linkage / Farthest Neighbour

 Average Linkage

 Centroid Linkage

 Hierarchical Clustering / Agglomerative Clustering.

 Non-clustering