Data mining techniques in financial fraud detection
shared
This Book is Out of Stock!
English

About The Book

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.
Piracy-free
Piracy-free
Assured Quality
Assured Quality
Secure Transactions
Secure Transactions
*COD & Shipping Charges may apply on certain items.
Review final details at checkout.
1513
1608
5% OFF
Paperback
Out Of Stock
All inclusive*
downArrow

Details


LOOKING TO PLACE A BULK ORDER?CLICK HERE