Paper Title : ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING
ISSN : 2394-2231
Year of Publication : 2021
MLA Style: K.E.Eswari., MCA., M.Phil.,M.E., P.Sivanandham "ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
APA Style: K.E.Eswari., MCA., M.Phil.,M.E., P.Sivanandham "ENHANCEMENT OF MARKET DATA PARTITIONING SCALABILITY AND HIGH DIAMENTIONALITY MANAGEMENT USING DEEP LEARNING " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
Forecasting store arrival is essential economic topics that have involved researchers’ concentration for several years. It involves a supposition that primary information widely offered in the precedent have various predictive associations to the expectations supply profits. Stock marketplace prediction is performing of annoying to decide the prospect worth of a concern stock or some other monetary tool traded on a replace. The unbeaten calculation of a stock's prospect cost might give up important income. The efficient-market theory suggests that stockpile rates replicate all presently accessible record and some cost modify that are not depend on recently exposed information thus are intrinsically changeable. Others diverge and those with this point of view have countless methods and technologies which supposedly let them to get prospect cost value. Our project has proposed ANN is a better suitable algorithm to predict stock market databases with better result.
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— Forecasting, Market data, Scalability, Marketplace, Machine Learning, ANN, Dimensionality.