Data Mining Algorithms

Abstract

In this Chapter, we will describe about several groups of the basic data mining algorithms. In the first section of dimension reduction and transformation algorithms, we will talk about the feature selection, feature extraction methods like principal component analysis and independent component analysis etc. In the section of machine learning algorithms, topics like logistic regression models, neural network models, fuzzy systems, ensemble methods, support vector machines and hybrid intelligent techniques etc. will be covered. Then, we will also talk about the clustering algorithms like hierarchical clustering, partition clustering spectral clustering, and their considerations. In the section of graph algorithms, topics like computer representations of graphs, breadth-first search algorithms, and depth-first search algorithms will be covered. This Chapter will conclude with the discussion of several popular numerical optimization algorithms like steepest descent method, Newton's method, sequential unconstrained minimization, reduced gradient methods, and interior-point methods.