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Coherence Evaluations for 'Model of Models' Methods
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- Type:
- Dataset
- 摘抄:
- CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/04/2022
- 更改日期:
- 11/04/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/04/2022
- 更改日期:
- 11/04/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/04/2022
- 更改日期:
- 11/04/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/04/2022
- 更改日期:
- 11/04/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/03/2022
- 更改日期:
- 11/17/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/03/2022
- 更改日期:
- 11/03/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
- Type:
- Dataset
- 摘抄:
- CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 11/02/2022
- 更改日期:
- 11/02/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)
- Type:
- Dataset
- 摘抄:
- CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 08/10/2022
- 更改日期:
- 08/10/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)
- Type:
- Dataset
- 摘抄:
- CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 08/10/2022
- 更改日期:
- 08/10/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)
- Type:
- Dataset
- 摘抄:
- CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 08/10/2022
- 更改日期:
- 08/10/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)