Agrawal, Mohit (2012) *Pattern Clustering using Soft-Computing Approaches.* BTech thesis.

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## Abstract

Clustering is the process of partitioning or grouping a given set of patterns into disjoint clusters. This is done such that patterns in the same cluster are alike and patterns belonging to two dierent clusters are dierent. . Clustering Process can be divided into two parts

Cluster formation

Cluster validation

The most trivial K-means algorithm is rst implemented on the data set obtained from UCI machine repository. The comparison is extended to Fuzzy C-means algorithm where each data is a member of every cluster but with a certain degree known as membership value. Finally, to obtain the optimal value of K Genetic K-means algorithm in implemented in which GA nds the value of K as generation evolves.The

ecieny of the three algorithms can be judged on the two measuring index such as :

the silhouette index and Davies-Bouldin Index .

Item Type: | Thesis (BTech) |
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Uncontrolled Keywords: | FCM:Fuzzy C-Means, GKA:Genetic K-Means Algorithm,CPU:Central Processing Unit |

Subjects: | Engineering and Technology > Computer and Information Science > Data Mining |

Divisions: | Engineering and Technology > Department of Computer Science |

ID Code: | 3744 |

Deposited By: | Mr Mohit Agrawal |

Deposited On: | 05 Jun 2012 12:11 |

Last Modified: | 05 Jun 2012 12:11 |

Supervisor(s): | Rath, S K |

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