Main Reference PaperAdaptive ensembling of semi-supervised clustering solutions, IEEE Transactions on Knowledge and Data Engineering, April 2017 [Java].
  • Closure based constraint propagation approach, random subspace based semi-supervised clustering ensemble framework and the adaptive semi-supervised clustering ensemble framework are proposed to deal with fully utilization of all useful must-link and cannot-link constraints, considering the high dimensional data with noise and be an adaptive process respectively.

+ Description
  • Closure based constraint propagation approach, random subspace based semi-supervised clustering ensemble framework and the adaptive semi-supervised clustering ensemble framework are proposed to deal with fully utilization of all useful must-link and cannot-link constraints, considering the high dimensional data with noise and be an adaptive process respectively.

  • To fully utilize all useful must-link and cannot-link constraints.

  • To the consider the high dimensional data with noise.

  • To use an adaptive process.

+ Aim & Objectives
  • To fully utilize all useful must-link and cannot-link constraints.

  • To the consider the high dimensional data with noise.

  • To use an adaptive process.

  • The technique of removing redundant constraints are contributed.

+ Contribution
  • The technique of removing redundant constraints are contributed.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1, & J2SE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1, & J2SE.

  • 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-Depending on the complexity of the project and requirements.

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

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