Main Reference PaperDisambiguation-Free Partial Label Learning, IEEE Transactions on Knowledge and Data Engineering, July 2017 [Java].
  • A new disambiguation-free approach to partial label learning is proposed that utilizes the well-known error-correcting output codes (ECOC) techniques to perform binary classification using training samples and coding dichotomy.

+ Description
  • A new disambiguation-free approach to partial label learning is proposed that utilizes the well-known error-correcting output codes (ECOC) techniques to perform binary classification using training samples and coding dichotomy.

  • To avoid the disambiguation in classification of partial label learning.

  • To build the binary classifier with respect to each column coding.

+ Aim & Objectives
  • To avoid the disambiguation in classification of partial label learning.

  • To build the binary classifier with respect to each column coding.

  • Proposed work is tested under the increased ECOC codeword length.

+ Contribution
  • Proposed work is tested under the increased ECOC codeword length.

  • 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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