The analysis of authorial style, termed stylometry, assumes that style is quantifiably
measurable for evaluation of distinctive qualities. Stylometry research has yielded several …

Principal component analysis (PCA) is often applied for analyzing data in the most diverse
areas. This work reports, in an accessible and integrated manner, several theoretical and …

This paper works on feature weighting approaches for naive Bayes text classifiers. Almost all
existing feature weighting approaches for naive Bayes text classifiers have some defects …

The sparse group lasso optimization problem is solved using a coordinate gradient descent
algorithm. The algorithm is applicable to a broad class of convex loss functions …

This article proposes a novel approach to linear dimension reduction for regression using
nonparametric estimation with positive-definite kernels or reproducing kernel Hilbert spaces …

The recent explosion of data size in number of records and attributes has triggered the
development of a number of Big Data analytics as well as parallel data processing methods …

For machine learning task, lacking sufficient samples mean the trained model has low
confidence to approach the ground truth function. Until recently, after the generative …

Recent researches have shown that deep forest ensemble achieves a considerable
increase in classification accuracy compared with the general ensemble learning methods …

Deep learning's performance on the imbalanced small data is substantially degraded by
overfitting. Recurrent neural networks retain better performance in such tasks by …

We propose a novel kernel approach to dimension reduction for supervised learning: feature
extraction and variable selection; the former constructs a small number of features from …