000			02686nam a22003253a 4500
001			UPMIN-00005905254
003			UPMIN
005			20230111115144.0
008			230111b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090		0	_aLG 993.5 2011 _bA64 F37
100			_aFarofaldino, Gay A. _91293
245			_aDissimilarity coefficients in hierarchical clustering for mixed and fuzzy feature variable / _cGay A. Farofaldino
300			_a90 leaves
500			_aThesis, Undergraduate (B.S. Applied Mathematics)-U.P. Mindanao.
520	3		_aYang's coefficient for mixed and fuzzy feature variable was modified in terms of the aggregation technique and the entropy-based distance function. There are four proposed dissimilarity coefficients which used Yang's coefficient for numerical attributes and fuzzy attributes while entropy such as Havrda-Charvat's structural a-entropy and Jensen-Shannon divergence for categorical attributes. The hierarchical clustering method was used for clustering mixed and fuzzy data. Single linkage clustering algorithm and UPGMA were employed to generate fuzzy dendrograms. The type of data has a significant effect on the clustering produced accompanied by the aggregation function used and the entropy measure employed. The dataset used in the study were small and large dataset. For small data, the proposed dissimilarity coefficients that used De Carvalho's extension of Ichino and Yaguchi's dissimilarity measure as aggregation produced better clustering solution in small data. On the other hand, for large data, the proposed dissimilarity coefficients that used the two aggregation function such as De Carvalho's dissimilarity measure and De Carvalho's extension of Ichino and Yamguchi's dissimilarity measure worked well in clustering. The proposed dissimilarity coefficients were compared to the original Yang's coefficient measures for mixed feature variable and fuzzy data to evaluate the effectiveness and efficiency of the propose dissimilarity coefficients. The proposed dissimilarity coefficients performed better with mixed and fuzzy feature variable compared to the original Yang's dissimilarity measures mixed and fuzzy data.
650	1	7	_aClustering. _9366
650	1	7	_aHierarchical clustering. _91294
650	1	7	_aDissimilarity coefficients. _91295
650	1	7	_aAggregation. _91296
650	1	7	_aEntropy. _91297
650	1	7	_aFuzzy data. _91298
650	1	7	_aJensen-Shannon divergence. _91299
650	1	7	_aClustering algorithm _91300
650	1	7	_aCluto package. _91301
650	1	7	_aSingle linkage algorithm. _91302
650	1	7	_aFuzzy datasets. _91303
942			_2lcc _cTHESIS
999			_c2686 _d2686