Main Reference PaperEffective learning model of user classification based on ensemble learning algorithms, Computing, 2019 [Java / Python / R]
  • This work proposes a hybrid learning model that improves the classification accuracy of the user to be sensitive to electric charge. It is implemented based on ensemble learning algorithms. An accurate user features are identified through the Sequential Floating Forward Selection algorithm (SFFS) and tagxedo tool respectively.

+ Description
  • This work proposes a hybrid learning model that improves the classification accuracy of the user to be sensitive to electric charge. It is implemented based on ensemble learning algorithms. An accurate user features are identified through the Sequential Floating Forward Selection algorithm (SFFS) and tagxedo tool respectively.

  • To classify the user belongs to electric charge sensitivity or not.

  • To improve the classification accuracy.

+ Aim & Objectives
  • To classify the user belongs to electric charge sensitivity or not.

  • To improve the classification accuracy.

  • By identifying whether a user is a charge-sensitive user and by making the precise marketing for this part of the users with service in place, the overall service of the grid enterprise will be improved.

+ Contribution
  • By identifying whether a user is a charge-sensitive user and by making the precise marketing for this part of the users with service in place, the overall service of the grid enterprise will be improved.

  • 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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