with the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. one of the major problems in text classification relates to the high dimensional feature spaces. therefore, the main goal of text classification is to reduce the dimensionality of features space. there are many feature selection methods. however...

The longwall mining method is one of the most applied methods in extracting low-inclined to high-inclined coal seams. Selection of the most suitable extraction equipment is very important in the economical, safety, and productivity aspects of mining operations. There are a lot of parameters affecting the selection of an extraction equipment in mechanized longwall mining in steeply inclined coal...

Effective methods for feature and model structure selection are very important for data-driven modeling, data mining, and system identification tasks. This paper presents a new method for selecting important variables (regressors) in nonlinear (dynamic) models with mixed discrete (categorical, fuzzy) and continuous inputs and outputs. The proposed method applies fuzzy association rule mining. T...

Data mining is a form of knowledge discovery required for solving problems in a specific domain. Classification is a technique used for discovering class labels of unknown data. Different methods for classification exists like bayesian, decision trees, rule based, neural networks etc. Before applying any mining technique, irrelevant and redundant features needs to be removed. Filtering is done ...

One of the most important steps involved in mining operations is to select an appropriate extraction method for mine resources. After choosing the extraction method, it is usually impossible to replace it with another one because it may be so expensive that implementation of the entire project could be economically impossible. Choosing a mining method depends on the geological and geometrical c...

In any mining application for useful information from databases, an increasing number of features (attributes) makes worse results and loses much time. We propose a feature selection technique which saves computation time and does not spoil effect of mining. We take an algorithm called Iterated Contextual Distances (ICD) [1], show its problems for practical applications, and propose a feature s...