Supervised Machine Learning (SML) is the search for algorithms that reason from externally
supplied instances to produce general hypotheses, which then make predictions about …

There is a necessity for analysis of a large amount of data in many fields such as healthcare,
business, industries, and agriculture. Therefore, the need of the feature selection (FS) …

Abstract Knowledge Discovery in Databases (KDD) covers various processes of exploring
useful information from voluminous data. These data may contain several inconsistencies …

The look for methodologies that can make inferences from externally supplied data develop
broad hypotheses that are subsequently used to create forecasts concerning future events is …

Today's artificial intelligence has become a commodity of and experimental studies, such as
mathematics. Machine learning is an application of artificial intelligence that allows …

The quick development of technology not only makes life easier but also raises several
security concerns, so cyber security has become very important and vital research area …

Abstract The" Digital Revolution" has blessed the human civilization with enormous amount
of" DATA". The challenges of automatically analyzing these data has augmented the need …

Real live clinical data often present itself with a number of usual challenges, such as class
imbalance, high dimensionality and missing data. There is the added complexity of the data …

Data enhancement is an essential operation when dealing with incomplete and imbalanced
data sets. Further classification on such data might prove to be a difficult task. This paper …

Named entity recognition (NER), as one of the crucial tasks of information extraction (IE), has
important effect on the quality of its subsequent applications such as answering the …