Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Several feature selection methods have been developed to extract the optimal features from
a dataset in medical datasets classification. Creating an efficient technique has become a …

Accurate and timely wheat yield prediction is of great importance to global food security.
Early prediction of wheat yield at a field scale is essential for site-specific precision …

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 …

Background and objective Medical data plays a decisive role in disease diagnosis. The
classification accuracy of high-dimensional datasets is often diminished by several …

Feature selection aims at selecting important features that can enhance learning
performance in data mining, pattern recognition, and machine learning. Filter feature …

In a carbon-constrained world, future uses of nuclear power technologies can contribute to
climate change mitigation as the installed electricity generating capacity and range of …

In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …