IEG 201402 ABIBA WAR with R

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Information about IEG 201402 ABIBA WAR with R
Business & Mgmt

Published on February 14, 2014

Author: informationexcellence



Information Excellence Group 2014 Spring "Business Analytics Industry Summit"
ABIBA Presentation WAR in R from Dr. Jay B Simha, CTO, ABIBA TECHNOLOGIES

ABIBA: WAR with R Dr Jay B Simha

WAR with R Power of open source!! Jay B.Simha Advanced Business Intelligence and Business Analytics

An year of active research in Artificial Intelligence is sufficient for any body to believe in god Alan J.Perlis MIT – AI genius

Unknown Known Knowledge Potential Why Analytics? Creativity Risk Domain Experts Opportunity Loss Known Unknown Knowledge Competence


Types of Analysis required Profiling • Who are my customers? Where they live? • How is the responder’s concentration,? • What behavioral similarity is there in segments? Diagnostics • What makes some thing to happen? • What caused a particular effect? Predictive • Who will respond to my next offer? • Who will not recharge next month and why? Prescriptive • What is the best offer for a group of customers? • Which is the best campaign for this customer

How R can be used? SOM/K-means models ACQUIRE SOM/K-means models/Random forests WALLET SHARE Decision tree/SVM RETENTION

WAR Applications Acquisition Telecom Retail Banking Insurance Hospitality Education Retention Wallet Share × × × × × × × × × × × × × × × ×

Methods for Madness CRISP DM SEMMA KDD

A KISS approach for modeling + SEMMA

What tools are needed with R RWeka Rule based scoring Build any where Score anywhere Free Community Edition The new lord Ganesha!!

Acquisition process

Acquisition process

Acquisition Build model on this Test model on this

Acquisition Exploratory Methods K-means clustering Self Organizing Maps Cross tabs/Pivots

Acquisition – Simulated data

Acquisition - SOM

Acquisition – SOM visualization

Acquisition - Kmeans

Acquisition - Kmeans

Acquisition – Kmeans visualization

Acquisition – Kmeans visualization







Wallet Share (X-Sell)

Take away • Data modeling and preprocessing is most important • All models are not equal • Few techniques are enough for WAR modeling • R and its friends are more than sufficient for most of the cases • Analytics is fun..Enjoy

Take away • Thanks to all people whom I can not thank individually who shared their expertise, slides, data and comments • All mistakes are mine, if you find any, in this talk or preso

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