Main Reference PaperSoft voting technique to improve the performance of global filter feature selection in text corpus, Applied Intelligence, 2018 [Java/Python/R]
  • A new Soft Voting Technique (SVT) is proposed to predict the class labels of the features. The proposed scheme obtains the results from the weighted average score (Soft Vote) of three methods, i.e. Odds Ratio (OR), Correlation Coefficient (CC), and GSS Coefficients (GSS). Next, it uses the Latent Semantic Analysis (LSA) at the initial level to reduce the high-dimensional feature space into a smaller one. The constructed final feature is used to predict the labels of features.

+ Description
  • A new Soft Voting Technique (SVT) is proposed to predict the class labels of the features. The proposed scheme obtains the results from the weighted average score (Soft Vote) of three methods, i.e. Odds Ratio (OR), Correlation Coefficient (CC), and GSS Coefficients (GSS). Next, it uses the Latent Semantic Analysis (LSA) at the initial level to reduce the high-dimensional feature space into a smaller one. The constructed final feature is used to predict the labels of features.

  • To predict the class labels of the features.

  • To improve the classification accuracy.

+ Aim & Objectives
  • To predict the class labels of the features.

  • To improve the classification accuracy.

  • An appropriate method is contributed to find out the selection of positive and negative features.

+ Contribution
  • An appropriate method is contributed to find out the selection of positive and negative features.

  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

+ Software Tools & Technologies
  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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