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portada Data Mining Techniques in Financial Fraud Detection
Type
Physical Book
Publisher
Author
Language
English
Pages
20
Format
Paperback
ISBN13
9783668709287

Data Mining Techniques in Financial Fraud Detection

Rohan Ahmed (Author) · Grin Verlag · Paperback

Data Mining Techniques in Financial Fraud Detection - Rohan Ahmed

New Book Imported to Taiwan
Delivery: 14 Oct - 22 Oct Shipping: 13 to 14 business days.
NT$ 719
NT$ 719

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Synopsis "Data Mining Techniques in Financial Fraud Detection"

Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.

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