Feature selection algorithms are the cornerstone of machine learning. By increasing the
properties of the samples and samples, the feature selection algorithm selects the significant …

Feature selection is a preprocessing step in classification tasks, which can reduce the
dimensionality of a dataset and improve the classification accuracy and efficiency. However …

Feature selection algorithms are of great importance in the field of machine learning.
Significant reduction of very large data is the main function of feature selection algorithms …

With the rapid development of information techniques, the dimensionality of data in many
application domains, such as text categorization and bioinformatics, is getting higher and …

Feature selection plays an important role in pattern classification. Its purpose is to remove
redundant features from data set as many as possible. The presence of useless features …

Many feature subset selection algorithms have been proposed and discussed for years.
However, the problem of finding the optimal feature subset from full data still remains to be a …

While extensive research in data mining has been devoted to developing better feature
selection techniques, none of this research has examined the intrinsic relationship between …

Feature selection as one of the key problems of data preprocessing is a hot research topic in
pattern recognition, machine learning, and data mining. Evaluating the relevance between …

Feature Selection is one of the preprocessing steps in machine learning tasks. Feature
Selection is effective in reducing the dimensionality, removing irrelevant and redundant …

The feature selection process can be considered a problem of global combinatorial
optimization in machine learning, which reduces the number of features, removes irrelevant …