Feature Selection Optimization Using a Hybrid Genetic Algorithm | IBOOK.PUB

Feature Selection Optimization Using a Hybrid Genetic Algorithm

The curse of dimensionality plays a vital role in data mining and pattern recognition applications. There are two methods which can address curse of dimensionality namely—feature reduction and feature selection (FS). The application of FS is such that it

PDF / 30,502,903 Bytes
816 Pages / 453.543 x 683.15 pts Page_size
8 Downloads / 244 Views

Recommend Documents

Hybrid Efficient Genetic Algorithm for Big Data Feature Selection Problems

184 95 946KB

Feature Selection for Vocal Segmentation Using Social Emotional Optimization Algorithm

186 3 1MB

A new ensemble feature selection approach based on genetic algorithm

183 98 510KB

A parallel hybrid krill herd algorithm for feature selection

201 70 2MB

A Robust Method for Multi-algorithmic Palmprint Recognition Using Exponential Genetic Algorithm-Based Feature Selection

153 61 32MB

Genetic Algorithm for Feature Selection and Parameter Optimization to Enhance Learning on Framingham Heart Disease Datas

150 30 10MB

A hybrid grasshopper and new cat swarm optimization algorithm for feature selection and optimization of multi-layer perc

149 78 4MB

A new BAT optimization algorithm based feature selection method for electrocardiogram heartbeat classification using emp

176 102 2MB

Optimal Reservoir Optimization Using Multiobjective Genetic Algorithm

174 94 58MB

Feature selection with multi-objective genetic algorithm based on a hybrid filter and the symmetrical complementary coef

162 40 1MB

Feature selection by using chaotic cuckoo optimization algorithm with levy flight, opposition-based learning and disrupt

141 17 3MB

Optimal feature selection for speech emotion recognition using enhanced cat swarm optimization algorithm

182 45 995KB