Outliers can significantly affect data mining performance. Outlier mining is an important issue in knowledge discovery and data mining and has attracted increasing interests in recent years. Class outlier is promising research direction. Few researches have been done in this direction. The paper theme has two main goals: the first one is to show the significance of Class Outlier Mining by discussing a comparative study between a Class Outlier detection method called Class Outlier Distance Based (CODB) and a conventional Outlier detection method. The second goal is to introduc
Outliers are observations that are rare or exceptional in some sense. Outlier Detection is the proce...
The outlier detection is an important and valuable research in KDD (Knowledge discover in database)....
ABSTRACT: Outliers are the data objects with different characteristics compared to other data object...
Outliers can significantly affect data mining performance. Outlier mining is an important issue in k...
Data Mining simply refers to the extraction of very interesting patterns of the data from the massiv...
In large datasets, identifying exceptional or rare cases with respect to a group of similar cases is...
Data Mining just alludes to the extraction of exceptionally intriguing patterns of the data from the...
While the field of data mining has been studied extensively, most of the work has concentrated on di...
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset ...
Outlier detection is an important research problem in data mining that aims to discover useful abnor...
This paper introduces two statistical outlier detection approaches by classes. Experiments on binar...
Abstract- Outlier detection is an active area for research in data set mining community. Finding out...
Outlier detection is a significant research area in data mining. An Outlier is a point or a set of p...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
Outliers are observations that are rare or exceptional in some sense. Outlier Detection is the proce...
The outlier detection is an important and valuable research in KDD (Knowledge discover in database)....
ABSTRACT: Outliers are the data objects with different characteristics compared to other data object...
Outliers can significantly affect data mining performance. Outlier mining is an important issue in k...
Data Mining simply refers to the extraction of very interesting patterns of the data from the massiv...
In large datasets, identifying exceptional or rare cases with respect to a group of similar cases is...
Data Mining just alludes to the extraction of exceptionally intriguing patterns of the data from the...
While the field of data mining has been studied extensively, most of the work has concentrated on di...
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset ...
Outlier detection is an important research problem in data mining that aims to discover useful abnor...
This paper introduces two statistical outlier detection approaches by classes. Experiments on binar...
Abstract- Outlier detection is an active area for research in data set mining community. Finding out...
Outlier detection is a significant research area in data mining. An Outlier is a point or a set of p...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
Outliers are observations that are rare or exceptional in some sense. Outlier Detection is the proce...
The outlier detection is an important and valuable research in KDD (Knowledge discover in database)....
ABSTRACT: Outliers are the data objects with different characteristics compared to other data object...