Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Updating URV decompositions in parallel
Parallel Computing
Downdating the Rank-Revealing URV Decomposition
SIAM Journal on Matrix Analysis and Applications
The nature of statistical learning theory
The nature of statistical learning theory
Matrix computations (3rd ed.)
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Updating a Generalized URV Decomposition
SIAM Journal on Matrix Analysis and Applications
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
SIAM Journal on Matrix Analysis and Applications
Generalizing discriminant analysis using the generalized singular value decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence
KDX: An Indexer for Support Vector Machines
IEEE Transactions on Knowledge and Data Engineering
Multiclass classifiers based on dimension reduction with generalized LDA
Pattern Recognition
Feature selection methods for text classification
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Text feature selection using ant colony optimization
Expert Systems with Applications: An International Journal
Improving Automatic Text Classification by Integrated Feature Analysis
IEICE - Transactions on Information and Systems
A class-feature-centroid classifier for text categorization
Proceedings of the 18th international conference on World wide web
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
A subspace kernel for nonlinear feature extraction
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Fast dimension reduction for document classification based on imprecise spectrum analysis
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An effective feature selection method for text categorization
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Classification probabilistic PCA with application in domain adaptation
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
PCA document reconstruction for email classification
Computational Statistics & Data Analysis
A novel chinese text feature selection method based on probability latent semantic analysis
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
A new model selection method for SVM
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
A text classification algorithm based on rocchio and hierarchical clustering
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Efficient feature selection filters for high-dimensional data
Pattern Recognition Letters
Hierarchical classification of web documents by stratified discriminant analysis
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Fast dimension reduction for document classification based on imprecise spectrum analysis
Information Sciences: an International Journal
Intelligent water drops algorithm for rough set feature selection
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Document categorization based on minimum loss of reconstruction information
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Minimizer of the Reconstruction Error for multi-class document categorization
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
Support vector machines (SVMs) have been recognized as one of the most successful classification methods for many applications including text classification. Even though the learning ability and computational complexity of training in support vector machines may be independent of the dimension of the feature space, reducing computational complexity is an essential issue to efficiently handle a large number of terms in practical applications of text classification. In this paper, we adopt novel dimension reduction methods to reduce the dimension of the document vectors dramatically. We also introduce decision functions for the centroid-based classification algorithm and support vector classifiers to handle the classification problem where a document may belong to multiple classes. Our substantial experimental results show that with several dimension reduction methods that are designed particularly for clustered data, higher efficiency for both training and testing can be achieved without sacrificing prediction accuracy of text classification even when the dimension of the input space is significantly reduced.