Databases Reduction

2D Dimensionality Reduction Methods without Loss

In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (...

Supervised Feature Extraction of Face Images for Improvement of Recognition Accuracy

Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...

Fuzzy-Rough set Approach to Attribute Reduction

Attribute Reduction has a significant role in different branches of artificial intelligence like machine learning, pattern recognition, data mining from databases etc. This paper deals with reduction of unimportant attribute(s) for classification and decision making, using Fuzzy-Rough set. A survey of Fuzzy-Rough set based methods for attribute reduction is presented here.

Partial Pattern Databases

Perimeters and pattern databases are two similar memorybased techniques used in single-agent search problems. We present partial pattern databases, which unify the two approaches into a single memorybased heuristic table. Our approach allows the use of any abstraction level. We achieve a three-fold reduction in the average number of nodes generated on the 13-pancake puzzle and a 27% reduction o...

Dimensionality Reduction of Accident Databases for Minimal Tradeoff in Prediction Accuracy