With the rapid development in technology, large amounts of high-dimensional data have
been generated. This high dimensionality including redundancy and irrelevancy poses a …

Many approaches of texture analysis by color or hyperspectral imaging are based on the
assumption that the image of a texture can be viewed as a multi-component image, where …

Color texture classification aims to recognize patterns by the analysis of their colors and their
textures. This process requires using descriptors to represent and discriminate the different …

Feature selection is one part of preprocessing which aims to reduce data dimensions. This
study aims to produce optimal performance of the best feature selection method …

In tabular data, certain challenges can negatively affect the quality of machine learning
models, such as high dimensionality, noisy, irrelevant, or repetitive features, interactions …

Özellik seçim işlemi, Makine Öğrenimi algoritmalarının çok boyutluluğun lanetinden (curse
of dimensionality) etkilenmemesi için çok önemlidir. Özellik seçim algoritmaları bu sorunu …

Attribute reduction is one important part researched in rough set theory. A reduct from a
decision table is a minimal subset of the conditional attributes which provide the same …