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 first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong
in 1994 and since then many CCEAs have been proposed and successfully applied to …

Feature selection is an important component of the machine learning domain, which selects
the ideal subset of characteristics relative to the target data by omitting irrelevant data. For a …

Feature selection is an important task for data analysis and information retrieval processing,
pattern classification systems, and data mining applications. It reduces the number of …

This paper proposes a modified binary particle swarm optimization (MBPSO) method for
feature selection with the simultaneous optimization of SVM kernel parameter setting …

Measuring the performance of a given classifier is not a straightforward or easy task.
Depending on the application, the overall classification rate may not be sufficient if one, or …

Feature selection is an important preprocessing step in machine learning and pattern
recognition. The ultimate goal of feature selection is to select a feature subset from the …

A well-performed demand forecasting can provide outpatient department (OPD) managers
with essential information for staff scheduling and rostering, considering the non-reservation …

Financial crisis prediction (FCP) plays a vital role in the economic phenomenon. The precise
prediction of the number and possibility of failing firms acts as an index of the growth and …

Background Selecting a subset of relevant properties from a large set of features that
describe a dataset is a challenging machine learning task. In biology, for instance, the …