One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

Data mining is one of the most explored and ongoing areas of research. Sentiment analysis
is a popular application of data mining, where the information regarding the customer's …

Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

The change in living standard made people to think on their physical health. Accordingly,
healthcare organizations are concentrating more on physical health of people in terms of …

Meta-heuristics are problem-independent optimization techniques which provide an optimal
solution by exploring and exploiting the entire search space iteratively. These techniques …

Abstract “Dimensionality” is one of the major problems which affect the quality of learning
process in most of the machine learning and data mining tasks. Having high dimensional …

Datasets comprise a collection of features; however, not all of these features may be
necessary. Feature selection is the process of identifying the most relevant features while …

Breast cancer is the most common among women that leads to death if not diagnosed at
early stages. Early diagnosis plays a vital role in decreasing the mortality rate globally …

Many search strategies have been exploited for the task of feature selection (FS), in an effort
to identify more compact and better quality subsets. Such work typically involves the use of …

As an important task in data mining, feature selection can improve the performance of
classification by eliminating the redundant or irrelevant features in original data. It is mainly …