Feature selection is an important data preprocessing step which is performed before a
learning algorithm is applied. The issue that has to be taken into consideration when …

Vast number of feature selection methods are available to evaluate the best subset of
features as the data in the real world is growing bigger and bigger. Feature selection …

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 …

Nowadays, a huge amount of data is generated every day in continuous manner in every
hour and if the data is not utilized in the right or meaningful manner then this is just like …

Feature selection is a procedure in machine learning to find a subset of features that help to
know the most important features of the data set for model construction. It removes irrelevant …

Feature selection, a method of dimensionality reduction, is nothing but collecting a range of
appropriate feature subsets from the total number of features. In this paper, a point by point …

Classification is a technique based on machine learning used to classify each item in a set
of data into a set of predefined classes or group. It is widely used in medical field to classify …

Feature Selection (FS) is an imperative issue in data mining and machine learning. It is an
inevitable task to shorter the number of features presented in the initial data set for better …

One of the most important classification problems is selecting proper features, ie features
that describe the classified object in the most straightforward way possible. Then, one of the …