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Full Description
A guide on how Predictive Analytics is applied and widely used by organizations such as banks, insurance providers, supermarkets and governments to drive the decisions they make about their customers, demonstrating who to target with a promotional offer, who to give a credit card to and the premium someone should pay for home insurance.
Contents
Introduction Project Planning Sample Selection Gathering and Preparing Data Understanding Relationships in Data Data Transformation (Pre-processing) Model Construction (Parameter Estimation) Validation, Model Performance and Cut-off Strategy Sample Bias and Reject Inference Implementation and Monitoring Multi-model (Fusion) Systems Further Topics Bibliography



