In this paper, we propose a novel method to select the most informativesubset of features,
which has little redundancy andvery strong discriminating power. Our proposed approach …

Feature selection plays an important part in improving the quality of learning algorithms in
machine learning and data mining. It has been widely studied in supervised learning …

Feature selection tries to find a subset of feature from a larger feature pool and the selected
subset can provide the same or even better performance compared with using the whole set …

Feature selection is an important step for data mining and machine learning. It can be used
to reduce the requirement of data measurement and storage, and defy the curse of …

Feature selection plays a critical role in data mining, driven by increasing feature
dimensionality in target problems. In this paper, we propose a new criterion for …

Feature selection as one of the key problems of data preprocessing is a hot research topic in
pattern recognition, machine learning, and data mining. Evaluating the relevance between …

In contrast to many popular feature selection algorithms that provide suboptimal solutions
according to some criterion, the OCFS algorithm can ensure optimal solutions according to …

Feature selection is a key task in statistical pattern recognition. Most feature selection
algorithms have been proposed based on specific objective functions which are usually …

Prediction plays a vital role in decision making. Correct prediction leads to right decision
making to save the life, energy, efforts, money and time. The right decision prevents physical …

This paper studies a new feature selection method for data classification that efficiently
combines the discriminative capability of features with the ridge regression model. It first sets …