Fisher linear discriminant analysis (FLDA) based on variance ratio is compared with scatter linear discriminant (SLDA) analysis based on determinant ratio. It is shown that each o...
Miroslaw Bober, Krzysztof Kucharski, Wladyslaw Ska...
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
This study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. We use a hybrid feature identification method, including syntac...
Jill Burstein, Karen Kukich, Susanne Wolff, Chi Lu...
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of different classes are obey to t...
Zhen Lei, ShengCai Liao, Dong Yi, Rui Qin, Stan Z....