TY  - BOOK
AU  - Ayman Taha Awad Allah Mohammed Farahat
AU  - Ali S. Hadi , 
AU  - Kareem Mohamed Darwish , 
AU  - Osman Mohamed Hegazy , 
TI  - Outlier values identification in data mining applications  / 
PY  - 2013///
CY  - Cairo : 
PB  - Ayman Taha Awad Allah Mohammed Farahat , 
KW  - Data mining
KW  - Measuring association
KW  - Out lievs detection categorical data
N1  - Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Systems; Issued also as CD
N2  - Outliers identification algorithms for categorical data usually take long computational time.They also strongly depend on parameter settings that require prior information about the data,e.g.,number of outliers in the data, maximum length of itemsets and/or minimum support for frequent itemsets.These input parameters are classified into two groups;(a)in-trinsic parameters which are required by an outliers detection method to produce a score for each object and(b) decision parameters which are required to decide if anobject is an out-lier based on the score
UR  - http://172.23.153.220/th.pdf
ER  -