## Pattern recognition with fuzzy objective function algorithms |

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### Contents

Models for Pattern Recognition | 1 |

Some Notes on Mathematical Models | 5 |

Uncertainty | 7 |

Copyright | |

22 other sections not shown

### Common terms and phrases

algorithms analysis applied Bayesian classifier c-means algorithms Calculate centroid classifier design cluster centers cluster validity clustering algorithms clustering criterion coefficient column conv(Bc convergence convex combination convex hull covariance matrix CWS clusters data points data set decision regions defined Definition denote discussed distance empirical error rate entropy equations estimate Euclidean norm example fc-NN finite fixed fuzzy c-means fuzzy c-partition fuzzy clustering fuzzy scatter fuzzy sets fuzzy subsets geometric hard c-partition hard clusters hyperplane indicate iterations Jm(U JVrm linear varieties mathematical measure membership function method Mfco minimize minimum models objective function observations optimal pair parameters partition pattern recognition Pf(F Picard iteration positive-definite matrix probability proof properties prototypes Ruspini's sample solutions statistical structure substructure Table Theorem uA(x unique UPGMA validity functional values vectors WGSS zero