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ITHEA Classification Structure > F. Theory of Computation  > F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY  > F.2.1 Numerical Algorithms and Problems 
SELECTING CLASSIFIERS TECHNIQUES FOR OUTCOME PREDICTION ...
By: Tatiana Shatovskaya (3854 reads)
Rating: (1.00/10)

Abstract: This paper presents an analysis of different techniques that is designed to aid a researcher in determining which of the classification techniques would be most appropriate to choose the ridge, robust and linear regression methods for predicting outcomes for specific quasi-stationary process.

Keywords: classification techniques, neural network, composite classifier

ACM Classification Keywords: F.2.1 Numerical Algorithms and Problems

Link:

SELECTING CLASSIFIERS TECHNIQUES FOR OUTCOME PREDICTION USING NEURAL NETWORKS APPROACH

Tatiana Shatovskaya

http://www.foibg.com/ijita/vol14/ijita14-3-p15.pdf

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F.2.1 Numerical Algorithms and Problems
article: Review of some problems on the complexity of simultaneous divisibility of linear · CONSTRUCTION OF SOME COMPOSITION PERMUTATIONS VIA LINEAR TRANSLATORS · A COMBINED EXTERIOR PENALTY FUNCTION – CONJUGATE GRADIENT ALGORITHM ... · DIFFERENTIAL EVOLUTION – PARTICLE SWARM OPTIMIZATION · ON THE COMPLEXITY OF SEARCH FOR CONJUNCTIVE RULES IN RECOGNITION PROBLEMS · SELECTING CLASSIFIERS TECHNIQUES FOR OUTCOME PREDICTION ... · MATRICIAL MODEL FOR THE STUDY OF LOWER BOUNDS · OPTIMAL CONTROL OF A SECOND ORDER PARABOLIC HEAT EQUATION · THE NEW SOFTWARE PACKAGE FOR DYNAMIC HIERARCHICAL CLUSTERING ... ·
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