Join Our WhatsApp Channel for Updates!
DATA MINING TECHNIQUES
| Institution | UNIVERSITY |
| Course | FORENSICS |
| Year | 1st Year |
| Semester | Unknown |
| Posted By | Brian Mike |
| File Type | |
| Pages | 21 Pages |
| File Size | 545.18 KB |
| Views | 5323 |
| Downloads | 0 |
| Price: |
Buy Now
 Buy via
whatsapp
|
Description
The paper presents application of data mining techniques to fraud analysis. We
present some classification and prediction data mining techniques which we
consider important to handle fraud detection. There exist a number of data
mining algorithms and we present statistics-based algorithm, decision treebased algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models
Below is the document preview.
-page04.png)
FORM 3 ENGLISH NOTES
Trending!
UPDATED FORM 3 ENGLISH NOTES
258 Pages
9030 Views
1 Downloads
1.27 MB
KCSE FORM 1 CHEMISTRY NOTES
Trending!
UPDATED KCSE FORM1 CHEMISTRY NOTES
117 Pages
6958 Views
1 Downloads
2.43 MB
KCSE FORM 2 CHEMISTRY NOTES
Trending!
UPDATED KCSE FORM2 CHEMISTRY NOTES
137 Pages
3430 Views
0 Downloads
1.73 MB
KCSE FORM 3 CHEMISTRY NOTES
Trending!
UPDATED KCSE FORM3 CHEMISTRY NOTES
262 Pages
4169 Views
2 Downloads
2.11 MB
KCSE FORM 4 CHEMISTRY NOTES
Trending!
UPDATED KCSE FORM4 CHEMISTRY NOTES
334 Pages
3136 Views
2 Downloads
4.44 MB