Main Reference PaperDistributed nearest neighbor classification for large-scale multi-label data on spark, Future Generation Computer Systems, 2018 [Python/Spark].
  • This work is proposed a distributed implementation of the Ml-knn to classify large-scale multi-label data using Spark. It relies on the nearest neighbor search method to gather statistical information, both in the train and test phases.

Description
  • This work is proposed a distributed implementation of the Ml-knn to classify large-scale multi-label data using Spark. It relies on the nearest neighbor search method to gather statistical information, both in the train and test phases.

  • To improve the prediction accuracy.

  • Reducing execution time.

  • To achieve the scalability.

Aim & Objectives
  • To improve the prediction accuracy.

  • Reducing execution time.

  • To achieve the scalability.

  • A proposed schemes is applied for a high-dimensional data.

Contribution
  • A proposed schemes is applied for a high-dimensional data.

  • 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.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

Leave Comment

Your email address will not be published. Required fields are marked *

clear formSubmit