ASSORTMENT OF DATA WITH BINARY TREE USING SUPERVISED LEARNING
Journal Title: International Journal of Civil Engineering and Technology - Year 2019, Vol 10, Issue 3
Abstract
Classification can be addressed by supervised & unsupervised approaches. Decision trees like binary tree follows supervised approach for these executions. There is necessity to classify the data and provide the consolidated update and delete. This paper talks about an empirical associated functionality. This work is completed by following standard norms of Software Engineering. Agile scum methodology helped to ensure exact implementation in Software Development Life Cycle (SDLC) as stated in Software Requirement specification (SRS).
Authors and Affiliations
BOSHRA F. ZOPON AL_BAYATY and MUROOJ KHALID IBRAHEEM
Keywords
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- EP ID EP46396
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