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 …

One of the challenges in data mining is the dimensionality of data, which is often very high
and prevalent in many domains, such as text categorization and bio-informatics. The high …

Feature selection has been the focus of interest for quite some time and much work has
been done. With the creation of huge databases and the consequent requirements for good …

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 has always been a critical step in pattern recognition, in which
evolutionary algorithms, such as the genetic algorithm (GA), are most commonly used …

Prediction plays a vital role in decision making. Correct prediction leads to right decision
making to save the life, energy, efforts, money and time. The right decision prevents physical …

Feature selection has been widely used in data mining and machine learning tasks to make
a model with a small number of features which improves the classifier's accuracy. In this …

Data mining is an inevitable step in knowledge discovery and it helps discovering hidden
and useful patterns among data. These days, the number of stored attributes for each entity …

Interacting features are those that appear to be irrelevant or weakly relevant with the class
individually, but when it combined with other features, it may highly correlate to the class …

Learning algorithms can be less effective on datasets with an extensive feature space due to
the presence of irrelevant and redundant features. Feature selection is a technique that …