A Comparative Study on Feature Selection in Text Categorization

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Text categorization with Support Vector Machines: Learning with many relevant features→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Machine learning in automated text categorization→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• ML-KNN: A lazy learning approach to multi-label learning→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Text Classification from Labeled and Unlabeled Documents using EM→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• A re-examination of text categorization methods→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• RCV1: A New Benchmark Collection for Text Categorization Research→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• An extensive empirical study of feature selection metrics for text classification→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• An Evaluation of Statistical Approaches to Text Categorization→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Support vector machines for spam categorization→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Inductive learning algorithms and representations for text categorization→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Adaptive Computation and Machine Learning→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• Mining Multi-label Data→A Comparative Study on Feature Selection in Text CategorizationLegacy edge — source detail unavailable
• A re-examination of text categorization methods→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• A re-examination of text categorization methods→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→A re-examination of text categorization methodsLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→Text Classification from Labeled and Unlabeled Documents using EMLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→Machine learning in automated text categorizationLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• The text mining handbook: advanced approaches in analyzing unstructured data→Support vector machines for spam categorizationLegacy edge — source detail unavailable
• ML-KNN: A lazy learning approach to multi-label learning→Machine learning in automated text categorizationLegacy edge — source detail unavailable
• ML-KNN: A lazy learning approach to multi-label learning→Inductive learning algorithms and representations for text categorizationLegacy edge — source detail unavailable
• Text Classification from Labeled and Unlabeled Documents using EM→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• Text Classification from Labeled and Unlabeled Documents using EM→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• An extensive empirical study of feature selection metrics for text classification→A re-examination of text categorization methodsLegacy edge — source detail unavailable
• An extensive empirical study of feature selection metrics for text classification→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• An extensive empirical study of feature selection metrics for text classification→Inductive learning algorithms and representations for text categorizationLegacy edge — source detail unavailable
• Machine learning in automated text categorization→A re-examination of text categorization methodsLegacy edge — source detail unavailable
• Machine learning in automated text categorization→Text Classification from Labeled and Unlabeled Documents using EMLegacy edge — source detail unavailable
• Machine learning in automated text categorization→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• Machine learning in automated text categorization→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• Machine learning in automated text categorization→Support vector machines for spam categorizationLegacy edge — source detail unavailable
• Machine learning in automated text categorization→Inductive learning algorithms and representations for text categorizationLegacy edge — source detail unavailable
• Text categorization with Support Vector Machines: Learning with many relevant features→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• RCV1: A New Benchmark Collection for Text Categorization Research→A re-examination of text categorization methodsLegacy edge — source detail unavailable
• RCV1: A New Benchmark Collection for Text Categorization Research→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• RCV1: A New Benchmark Collection for Text Categorization Research→Machine learning in automated text categorizationLegacy edge — source detail unavailable
• RCV1: A New Benchmark Collection for Text Categorization Research→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• Support vector machines for spam categorization→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• Inductive learning algorithms and representations for text categorization→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• Inductive learning algorithms and representations for text categorization→Text categorization with Support Vector Machines: Learning with many relevant featuresLegacy edge — source detail unavailable
• Adaptive Computation and Machine Learning→Support vector machines for spam categorizationLegacy edge — source detail unavailable
• Mining Multi-label Data→ML-KNN: A lazy learning approach to multi-label learningLegacy edge — source detail unavailable
• Mining Multi-label Data→An Evaluation of Statistical Approaches to Text CategorizationLegacy edge — source detail unavailable
• Mining Multi-label Data→RCV1: A New Benchmark Collection for Text Categorization ResearchLegacy edge — source detail unavailable