Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

Feature selection (FS) is an important data pre-processing technique in classification. In
most cases, FS can improve classification accuracy and reduce feature dimension, so it can …

Wind energy is one of the sources which is still in development in Brazil. However, it already
represents 17% of the National Interconnected System. Due to the high level of uncertainty …

Feature selection is a multi-objective optimization problem since it has two conflicting
objectives: maximizing the classification accuracy and minimizing the number of the …

By identifying relevant features from the original data, feature selection methods can
maintain or improve the classification accuracy and reduce the dimensionality. Recently …

Abstract Software Fault Prediction (SFP) is an important process to detect the faulty
components of the software to detect faulty classes or faulty modules early in the software …

Feature selection is a pre-processing technique used to remove unnecessary
characteristics, and speed up the algorithm's work process. A part of the technique is carried …

To reduce the dimensionality of high-dimensional data and enhance its classification
accuracy, feature selection can be regarded as a multiobjective optimization problem that …

As a typical category of data scarcity, small sample often makes it difficult to build a reliable
machine learning model in credit risk assessment, and thus many virtual sample generation …

As online P2P loans in automotive financing grows, there is a need to manage and control
the credit risk of the personal auto loans. In this paper, the personal auto loans data sets on …