A comparative study between rough and decision tree classifiers
Rule-based classification system (RBC) has been widely used in many real world applications because of the easy interpretability of rules.RBC mines a collection of rule via knowledge which is hidden in dataset in order to accurately map new cases to the decision class.In the real world, the number o...
Saved in:
Main Author: | Mohamad Mohsin, Mohamad Farhan |
---|---|
Format: | Monograph |
Language: | English English |
Published: |
Universiti Utara Malaysia
2008
|
Subjects: | |
Online Access: | http://repo.uum.edu.my/7807/1/fAR.pdf http://repo.uum.edu.my/7807/3/1.Mohamad%20Farhan.pdf http://repo.uum.edu.my/7807/ http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000301019 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comparing the knowledge quality in rough classifier and decision tree classifier
by: Mohamad Mohsin, Mohamad Farhan, et al.
Published: (2008) -
A comparative study of apriori and rough classifier for data mining
by: Mohamad Farhan Mohamad Mohsin,, et al.
Published: (2008) -
Parameterizable decision tree classifier on NETFPGA
by: Monemi, A., et al.
Published: (2013) -
Single decision tree classifiers' accuracy on medical data
by: Hasan, Md Rajib, et al.
Published: (2015) -
Single decision tree classifiers' accuracy on medical data
by: Hasan, Md Rajib, et al.
Published: (2015)