'Fraudulent credit card transactions' diaporamas de présentation

Chapter 11: E-Commerce

Chapter 11: E-Commerce. Learning Objectives. Explain what e-commerce is and describe some of the advantages and disadvantages involved with implementing e-commerce. Identify a variety of e-commerce business models and discuss their differences.

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Learning To Predict rare events in event sequences

Learning To Predict rare events in event sequences. By Gary M Weiss and Haym Hirsh Presented by Veena Raja Rathna. Contents. Aim & Introduction to the problem Basic problem Formulation Definitions & Evaluation metrics Learning methods

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Chapter 11

588 views • 21 slides

Inductive Learning of Rules

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A Guideline of Visa Chargeback Policy Changes

Merchants are beginning to fight back, primarily through Chargeback Companies and lawsuits against the Cardholders, Issuing banks and even the Visa and MasterCard branded networks. One such lawsuit claims that “major credit card companies and the nation’s largest banks conspired to shift liability for fraudulent credit card transactions in the U.S. to merchants. The complaint claims that the move to cards that include electronic chips designed to be more secure—so-called EMV chips—has been plagued by technical glitches and used as cover to illegally shift fraud-protection costs.”

86 views • 8 slides

Rare Category Detection in Machine Learning

Rare Category Detection in Machine Learning. Prafulla Dawadi Topics in Machine Learning. Outline. Part I Examples Rare Class, Imbalanced Class, Outliers Part II (Rare)Category Detection Part III Kernel Density Estimation Mean Shift and Hierarchal Mean Shift

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DATA MINING LECTURE 2

DATA MINING LECTURE 2. Data Preprocessing Exploratory Analysis Post-processing. What is Data Mining?. Data mining is the use of efficient techniques for the analysis of very large collections of data and the extraction of useful and possibly unexpected patterns in data .

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