Gray Codes for Partial Match and Range Queries
IEEE Transactions on Software Engineering
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Computational Methods for Intelligent Information Access
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Algorithm 805: computation and uses of the semidiscrete matrix decomposition
ACM Transactions on Mathematical Software (TOMS)
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Nonorthogonal decomposition of binary matrices for bounded-error data compression and analysis
ACM Transactions on Mathematical Software (TOMS)
Learning Image Components for Object Recognition
The Journal of Machine Learning Research
Document clustering using nonnegative matrix factorization
Information Processing and Management: an International Journal
Boolean Factor Analysis by Attractor Neural Network
IEEE Transactions on Neural Networks
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In this paper we compare the performance of several dimension reduction techniques which are used as a tool for feature extraction. The tested methods include singular value decomposition, semi-discrete decomposition, non-negative matrix factorization, novel neural network based algorithm for Boolean factor analysis and two cluster analysis methods as well. So called bars problem is used as the benchmark. Set of artificial signals generated as a Boolean sum of given number of bars is analyzed by these methods. Resulting images show that Boolean factor analysis is upmost suitable method for this kind of data.