Software fault prediction using different techniques has been done by various researchers
previously. It is observed that the performance of these techniques varied from dataset to …

Several classification techniques have been investigated and evaluated earlier for the
software fault prediction. These techniques have produced different prediction accuracy for …

Background and objective Risk prediction models aim at identifying people at higher risk of
developing a target disease. Feature selection is particularly important to improve the …

This study evaluates several feature ranking techniques together with some classifiers
based on machine learning to identify relevant factors regarding the probability of …

Determining the most appropriate learning technique (s) is vital for the accurate and effective
software fault prediction (SFP). Earlier techniques used for SFP have reported varying …

Feature selection is a key step when dealing with high-dimensional data. In particular, these
techniques simplify the process of knowledge discovery from the data by selecting the most …

The capability of lower order Krawtchouk moment‐based shape features has been
analyzed. The behaviour of 1D and 2D Krawtchouk polynomials at lower orders is observed …

The high dimensionality of software metric features has long been noted as a data quality
problem that affects the performance of software defect prediction (SDP) models. This …

Background and objective Risk prediction models aim at identifying people at higher risk of
developing a target disease. Feature selection is particularly important to improve the …

Context. Software defect prediction aims to find defect prone source code, and thus reduce
the effort, time and cost involved with ensuring the quality of software systems. Both code …