Improved K-Modes Clustering Method Based on Chi-square Statistics
2010
This paper proposes an improved K-Modes clustering method based on Chi-square statistics, using Chi-square statistics to characterize the relationship between the attributes of data objects. On this basis, the new distance measure is proposed, The distance measure method not only take into account the value of an attribute of an object different from itself, but also take into account other attributes’ influence, which can meet the practical problems. The experimental results show that the proposed clustering method is effective, it can improve the accuracy of the clustering.
Keywords:
- Hierarchical clustering
- Artificial intelligence
- Cluster analysis
- Correlation clustering
- k-medians clustering
- FLAME clustering
- CURE data clustering algorithm
- Statistics
- Canopy clustering algorithm
- Pattern recognition
- Mathematics
- Brown clustering
- Consensus clustering
- Constrained clustering
- Computer science
- Data mining
- Fuzzy clustering
- Correction
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