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Genetic learning of fuzzy cognitive maps
Fuzzy cognitive maps (FCMs) are a very convenient, simple, and powerful tool for simulation and analysis of dynamic systems. They were originally developed in 1980 by Kosko, and since thenExpand
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CAIM discretization algorithm
  • L. Kurgan, K. Cios
  • Computer Science
  • IEEE Transactions on Knowledge and Data…
  • 1 February 2004
The task of extracting knowledge from databases is quite often performed by machine learning algorithms. The majority of these algorithms can be applied only to data described by discrete numericalExpand
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MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins
Motivation: Molecular recognition features (MoRFs) are short binding regions located within longer intrinsically disordered regions that bind to protein partners via disorder-to-order transitions.Expand
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SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
BackgroundProtein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However,Expand
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A survey of Knowledge Discovery and Data Mining process models
Knowledge Discovery and Data Mining is a very dynamic research and development area that is reaching maturity. As such, it requires stable and well-defined foundations, which are well understood andExpand
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Prediction of structural classes for protein sequences and domains - Impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy
This paper addresses computational prediction of protein structural classes. Although in recent years progress in this field was made, the main drawback of the published prediction methods is aExpand
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Prediction of protein structural class using novel evolutionary collocation-based sequence representation
Knowledge of structural classes is useful in understanding of folding patterns in proteins. Although existing structural class prediction methods applied virtually all state-of-the-art classifiers,Expand
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Impact of imputation of missing values on classification error for discrete data
Numerous industrial and research databases include missing values. It is not uncommon to encounter databases that have up to a half of the entries missing, making it very difficult to mine them usingExpand
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Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences
BackgroundKnowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues,Expand
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Data Mining: A Knowledge Discovery Approach
This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem andExpand
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