Data Mining for Forecasting OGDCL Share Prices Using WEKA

被引：1

作者：

Rehman, Iffraah ^{[1
]}

Soomro, Tariq Rahim ^{[1
]}

机构：

[1] Inst Business Management, CCSIS, Karachi, Pakistan

来源：

2019 13TH INTERNATIONAL CONFERENCE ON MATHEMATICS, ACTUARIAL SCIENCE, COMPUTER SCIENCE AND STATISTICS (MACS-13) | 2019年

关键词：

Data Mining; WEKA; Forecasting; OGDCL;

D O I：

10.1109/macs48846.2019.9024780

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Data mining is one of the emerging techniques that is being used in different areas science, education etc. with different machine learning algorithms. Different tools are available for performing data mining, one of which is WEKA. The aim of this paper is to use WEKA tool for data analysis of OGDCL stock prices. Two forecasting algorithms i.e. SMOreg and Multilayer perceptron has been used. Open, high, low and close price of OGDC stock share has been predicted for ten days. The results for obtained from both algorithms have been compared. It was found that SMOreg provides the most accurate result of the two algorithms for the given dataset. Further analysis of different forecasting algorithm for more accurate result has to done in future.

引用

页数：7

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