Space or time adaptive signal processing by neural network models
AIP Conference Proceedings 151 on Neural Networks for Computing
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Elements of information theory
Elements of information theory
C4.5: programs for machine learning
C4.5: programs for machine learning
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Classification Using Adaptive Wavelets for Feature Extraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Enhancements to the data mining process
Enhancements to the data mining process
On the Stability of Source Separation Algorithms
Journal of VLSI Signal Processing Systems
Effective Data Mining Using Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Mutual Information in Learning Feature Transformations
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Image Feature Extraction by Sparse Coding and Independent Component Analysis
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Knowledge extraction from local function networks
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A connectionist approach to generating oblique decision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Integrated feature architecture selection
IEEE Transactions on Neural Networks
Principal feature classification
IEEE Transactions on Neural Networks
Efficient source adaptivity in independent component analysis
IEEE Transactions on Neural Networks
Input feature selection for classification problems
IEEE Transactions on Neural Networks
On the strength of hyperclique patterns for text categorization
Information Sciences: an International Journal
EURASIP Journal on Advances in Signal Processing
Feature extraction with weighted samples based on independent component analysis
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Kernel discriminant analysis for regression problems
Pattern Recognition
Dimensionality reduction based on ICA for regression problems
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Generalization of linear discriminant analysis using Lp-norm
Pattern Recognition Letters
| Hi-index | 0.00 |
In manipulating data such as in supervised learning, we often extract new features from the original features for the purpose of reducing the dimensions of feature space and achieving better performance. In this paper, we show how standard algorithms for independent component analysis (ICA) can be appended with binary class labels to produce a number of features that do not carry information about the class labels驴these features will be discarded驴and a number of features that do. We also provide a local stability analysis of the proposed algorithm. The advantage is that general ICA algorithms become available to a task of feature extraction for classification problems by maximizing the joint mutual information between class labels and new features, although only for two-class problems. Using the new features, we can greatly reduce the dimension of feature space without degrading the performance of classifying systems.