Classification and Clustering in R

Package contents:

• classify.r: Build a predictive model for a bank's marketing department using SVM classifier.
• kmeans.r: Identify distinct patterns of electric power consumption

Classification task - Predict successful conversion

Build a predictive model for a bank's marketing department using SVM classifier.

Data Set Information:

The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed.
The classification goal is to predict if the client will subscribe (yes/no) a term deposit (variable y).
More information can be obtained from the UCI website.

Clustering task

Identify distinct patterns of electric power consumption

Dataset Information:

Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years (between December 2006 and November 2010 (47 months)). Different electrical quantities and some sub-metering values are available. More information can be obtained from the UCI website.
Goal is to identify clusters in consumption patterns