In the diagnosis and treatment of cancer, cancer classification is a vital issue. Gene selection
is much needed to solve the high dimensionality issue in microarray data, small sample size …

Feature selection techniques play a vital role in the processes that deal with enormous
amounts of data. These techniques have become extremely crucial and necessary for data …

Diagnosing depression at an early stage is crucial and majorly depends on the clinician's
skill. The present work aims to develop an automated tool for assisting the diagnostic …

Feature processing is an important step for modeling and can improve the accuracy of
machine learning models. Feature extraction methods can effectively extract features from …

Financial credit risk analysis management has been a foremost influence with a lot of
challenges, especially for banks reducing their principal loss. In this study, the machine …

In the 20th century, it is evident that there is a massive evolution of chronic diseases. The
data mining approaches beneficial in making some medicinal decisions for curing diseases …

Defects that occur in software products are a universal occurrence. Software defect
prediction is usually carried out to determine the performance, accuracy, precision and …

This paper proposes a two-stage framework for developing hybrid approaches to solve the
three printed circuit board assembly (PCBA) problems, component sequencing problem …

During the past decade, assigning objects to one of several predefined classes with higher
accuracy has received considerable focus among researchers. Hence, many algorithms …

Many features can be extracted from the massive volume of data in different types that are
available nowadays on social media. The growing demand for multimedia applications was …