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文章基本信息

  • 标题:Performance of machine learning methods for classification tasks
  • 本地全文:下载
  • 作者:B. Krithika ; Dr. V. Ramalingam ; K. Rajan
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2013
  • 卷号:5
  • 期号:06
  • 页码:448-454
  • 出版社:Engg Journals Publications
  • 摘要:In this paper, the performance of various machine learning methods on pattern classification and recognition tasks are proposed. The proposed method for evaluating performance will be based on the feature representation, feature selection and setting model parameters. The nature of the data, the methods of feature extraction and feature representation are discussed. The results of the Machine Learning algorithms on the classification task are analysed. The performance of Machine Learning methods on classifying Tamil word patterns, i.e., classification of noun and verbs are analysed. The software WEKA (data mining tool) is used for evaluating the performance. WEKA has several machine learning algorithms like Bayes, Trees, Lazy, Rule based classifiers.
  • 关键词:Machine learning; pattern classification; pattern recognition; feature representation; feature selection; setting model parameters; Tamil word patterns; noun; verbs and Weka.
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