Robust PRIDIT scoring method for classification fraud cases in financial data
Increasing number of fraud cases could jeopardize business solvency. Identification of fraud using effective statistical methods, such as classification, can protect organisations from this pitfall. However, identifying fraud cases can be a statistical challenge due to several characteristics of fin...
Saved in:
Main Author: | Tukiman, Norbaiti |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/101815/1/NorbaitiTukimanPFS2022.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Logistic regression methods for classification of imbalanced data sets
by: Santi Puteri Rahayu, -
Published: (2012) -
Several Robust Techniques In Two-Groups
Unbiased Linear Classification
by: Okwonu, Friday Zinzendoff
Published: (2013) -
A robust estimation method of location and scale with application in monitoring process variability
by: Mohd Salleh, Rohayu
Published: (2013) -
Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
by: Rokhsaneh, Yousef Zehi
Published: (2023) -
An enhanced robust association rules method for missing values imputation in Arabic language data set
by: Salem, Awsan Thabet
Published: (2023)