Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Zhexue Huang low
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Citation edge evidence
- Survey of Clustering Algorithms→Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical ValuesLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical ValuesLegacy edge — source detail unavailable
- K-means clustering algorithms: A comprehensive review, variants analysis, and advances in…→Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical ValuesLegacy edge — source detail unavailable
- The k-means Algorithm: A Comprehensive Survey and Performance Evaluation→Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical ValuesLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→Pattern Recognition with Fuzzy Objective Function AlgorithmsLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→Algorithms for Clustering DataLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→Finding Groups in DataLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→A General Coefficient of Similarity and Some of Its PropertiesLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→Cluster Analysis for ApplicationsLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→BIRCHLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→An Examination of Procedures for Determining the Number of Clusters in a Data SetLegacy edge — source detail unavailable
- Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values→BIRCHLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→Algorithms for Clustering DataLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→An Examination of Procedures for Determining the Number of Clusters in a Data SetLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→BIRCHLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→Pattern Recognition with Fuzzy Objective Function AlgorithmsLegacy edge — source detail unavailable
- Algorithms for Clustering Data→An Examination of Procedures for Determining the Number of Clusters in a Data SetLegacy edge — source detail unavailable
- Algorithms for Clustering Data→Cluster Analysis for ApplicationsLegacy edge — source detail unavailable
- BIRCH→Finding Groups in DataLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→A Survey of Clustering Data Mining TechniquesLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→Algorithms for Clustering DataLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→An Examination of Procedures for Determining the Number of Clusters in a Data SetLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→A General Coefficient of Similarity and Some of Its PropertiesLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→BIRCHLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→Pattern Recognition with Fuzzy Objective Function AlgorithmsLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→Cluster Analysis for ApplicationsLegacy edge — source detail unavailable
- Survey of Clustering Algorithms→BIRCHLegacy edge — source detail unavailable
- BIRCH→Finding Groups in DataLegacy edge — source detail unavailable
- K-means clustering algorithms: A comprehensive review, variants analysis, and advances in…→The k-means Algorithm: A Comprehensive Survey and Performance EvaluationLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| C4.5: Programs for Machine Learning | 1992 | 23,704 |
| Pattern Recognition with Fuzzy Objective Function Algorithms | 1981 | 16,856 |
| Algorithms for Clustering Data | 1990 | 7,849 |
| Finding Groups in Data | 1990 | 7,270 |
| A General Coefficient of Similarity and Some of Its Properties | 1971 | 5,334 |
| Cluster Analysis for Applications | 1973 | 5,152 |
| BIRCH | 1996 | 3,918 |
| An Examination of Procedures for Determining the Number of Clusters in a Data Set | 1985 | 3,889 |
| BIRCH | 1996 | 2,075 |
What cites it, inside the corpus
Links
Topics
| Advanced Clustering Algorithms Research | Computer Science |
| Data Mining Algorithms and Applications | Computer Science |
| Data Management and Algorithms | Computer Science |
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Nothing in this record contradicts itself and no field we check is missing.
- supports1 author record(s) attached.
- supports40 reference(s) recorded.
- neutralThe DOI carries no year to check against.
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Provenance
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