ANALISIS KELOMPOK UNTUK DATA KATEGORIK BERDASARKAN ALGROITMA VEKTOR HAMMING DISTANCE (Studi Kasus : Klasifikasi Hewan Berdasarkan Morfologi dan Karakteristik Umum)
Clustering analysis using K-Means clustering methods which using mean as the center of cluster doesn�t have any meaning anymore if the method is used for the categorical data. Clustering analysis using Hamming distance vector algorithm is only for categorical dataset. Theory...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2014
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| Summary: | Clustering analysis using K-Means clustering methods which using mean
as the center of cluster doesn�t have any meaning anymore if the method is used
for the categorical data. Clustering analysis using Hamming distance vector
algorithm is only for categorical dataset. Theory that used in this algorithm is
based on coding theory. It doesn�t need any model or convergence criteria for this
algorithm. This algorithm is the alternate way for older method : K-Modes and
Autoclass. The case studies in this thesis is animal classification based on their
morphology and common characteristic, the purpose of the classification is
grouping some animal into subpopulation. Thus, the result can be a reference to
studing animal from their simmilarities. |
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