Model-Based Gaussian and Non-Gaussian Clustering
Jeffrey D. Banfield low, Adrian E. Raftery
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Citation edge evidence
- Finite Mixture Models→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Model-Based Clustering, Discriminant Analysis, and Density Estimation→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture…→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Multivariate Data Analysis→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- A Survey of Clustering Data Mining Techniques→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- An entropy criterion for assessing the number of clusters in a mixture model→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Unsupervised learning of finite mixture models→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Latent Class Cluster Analysis→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Assessing a mixture model for clustering with the integrated completed likelihood→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- A review of clustering techniques and developments→Model-Based Gaussian and Non-Gaussian ClusteringLegacy edge — source detail unavailable
- Model-Based Gaussian and Non-Gaussian Clustering→Algorithms for Clustering DataLegacy edge — source detail unavailable
- Model-Based Gaussian and Non-Gaussian Clustering→Mixture models : inference and applications to clusteringLegacy 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→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
- Finite Mixture Models→Model-Based Clustering, Discriminant Analysis, and Density EstimationLegacy edge — source detail unavailable
- Finite Mixture Models→Assessing a mixture model for clustering with the integrated completed likelihoodLegacy edge — source detail unavailable
- Finite Mixture Models→mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture…Legacy edge — source detail unavailable
- Model-Based Clustering, Discriminant Analysis, and Density Estimation→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
- Model-Based Clustering, Discriminant Analysis, and Density Estimation→An entropy criterion for assessing the number of clusters in a mixture modelLegacy edge — source detail unavailable
- Model-Based Clustering, Discriminant Analysis, and Density Estimation→Assessing a mixture model for clustering with the integrated completed likelihoodLegacy edge — source detail unavailable
- Unsupervised learning of finite mixture models→Finite Mixture ModelsLegacy edge — source detail unavailable
- Unsupervised learning of finite mixture models→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
- Unsupervised learning of finite mixture models→An entropy criterion for assessing the number of clusters in a mixture modelLegacy edge — source detail unavailable
- Unsupervised learning of finite mixture models→Assessing a mixture model for clustering with the integrated completed likelihoodLegacy edge — source detail unavailable
- An entropy criterion for assessing the number of clusters in a mixture model→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
- Assessing a mixture model for clustering with the integrated completed likelihood→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
- Assessing a mixture model for clustering with the integrated completed likelihood→An entropy criterion for assessing the number of clusters in a mixture modelLegacy edge — source detail unavailable
- mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture…→Model-Based Clustering, Discriminant Analysis, and Density EstimationLegacy edge — source detail unavailable
- mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture…→Assessing a mixture model for clustering with the integrated completed likelihoodLegacy edge — source detail unavailable
- A review of clustering techniques and developments→Algorithms for Clustering DataLegacy edge — source detail unavailable
- Latent Class Cluster Analysis→Mixture models : inference and applications to clusteringLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Algorithms for Clustering Data | 1990 | 7,849 |
| Mixture models : inference and applications to clustering | 1988 | 2,079 |
What cites it, inside the corpus
Links
Topics
| Bayesian Methods and Mixture Models | Computer Science |
| Advanced Clustering Algorithms Research | Computer Science |
| Bayesian Modeling and Causal Inference | Computer Science |
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