General Set Covering for Feature Selection in Data Mining

Feature Selection in Data Mining

Feature selection methods for mining bioinformatics data

Feature selection methods for mining bioinformatics data – p. 1/3

Visual Learning by Set Covering Machine with Efficient Feature Selection

In this paper, we propose a new visual learning method for real-world object recognition task. Our method is based on the Set Covering Machine (SCM), to make the learning time shorter than the methods based on commonly used trial-and-error algorithms, such as genetic programming and reinforcement learning. Generally, the process of visual learning is quite time-consuming because image data cons...

Data mining for feature selection in gene expression autism data

The paper presents application of data mining methods for recognizing the most significant genes and gene sequences (treated as features) stored in a dataset of gene expression microarray. The investigations are performed for autism data. Few chosen methods of feature selection have been applied and their results integrated in the final outcome. In this way we find the contents of small set of ...

Classification and Comparative Study of Data Mining Classifiers with Feature Selection on Binomial Data Set

This paper describes about the performance analysis of different data mining classifiers before and after feature selection on binomial data set. Three data mining classifiers Logistic Regression, SVM and Neural Network classifiers are considered in this paper for classification. The Congressional Voting Records data set is a binomial data set investigated in this study is taken from UCI machin...