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Nirmala C. R
Bapuji Institute of Engineering and Technology

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A computing model for trend analysis in stock data stream classification Abdul Razak; Nirmala C. R
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1602-1609

Abstract

For several decades, many statistical and scientific efforts took place for the better analysis or prediction of stock trading. But still it is open to offer new avenues for the scientists to rethink and discover new inferences by adopting latest technological scenarios. In this regard, this paper is trying to apply classification techniques on stock data stream through feature extraction for the trend analysis. The proposed work is involving k-means for clustering samples into two clusters (the stocks in trend as one cluster and another on as stocks not in trend). The trend analysis is done based on density estimation of the stocks with respect to sectors. A well-known data representation method that is histogram is used to represent the sector which is in trend. This work has been implemented and experimented by considering live NSE (India) data using python and its related tools.
Co-Authors Abdul Razak