Over the past several decades the dramatic increase in the availability of computational
resources, coupled with the maturation of machine learning, has profoundly impacted …

Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …

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 …

Since different features may require different costs, the cost-sensitive feature selection
problem become more and more important in real-world applications. Generally, it includes …

Feature selection is an important data-preprocessing technique in classification problems
such as bioinformatics and signal processing. Generally, there are some situations where a …

Nowadays, large amount of data is available everywhere. Therefore, it is very important to
analyze this data in order to extract some useful information and to develop an algorithm …

Feature selection has been a significant task for data mining and pattern recognition. It aims
to choose the optimal feature subset with the minimum redundancy and the maximum …

High-dimensional data is ubiquitous in scientific research and industrial production fields. It
brings a lot of information to people, at the same time, because of its sparse and …

Dissatisfaction is the first step of progress, this statement serves to be the base of using
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …

Recommender systems attempt to guide users in decisions related to choosing items based
on inferences about their personal opinions. Most existing systems implicitly assume the …