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Data Mining Forecasting Oil and Gas Development Company Ltd. Share Prices Using Orange

EasyChair Preprint 3588

5 pagesDate: June 10, 2020

Abstract

Data Mining is one of the emerging technology that is being used in the field of Data Science. In data mining, we can be used multiple algorithms of machine learning. There are many tools available for the purpose of data mining which one of the Orange3. The purpose of this paper is to use Orange3 for the Analysis of Oil and Gas share prices of the stock exchange. In this paper, four algorithms are being used for the purpose of predicting the share prices of OGDCL in the exchange market. The result of both algorithms are compared by each other and then it was found the best result of the algorithm is Naïve Bayes and Neural Network. It was found the most accurate and perfect result gives the Naïve Bayes and Neural Network. For the given Dataset. In the future, I will do different analyses for the purpose of predict accurate share price results.

Keyphrases: Classification, Data Mining, Forecasting, ORANGE3, STOCK-SHARE-PRICES

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:3588,
  author    = {Muhammad Farooq Ishaq},
  title     = {Data Mining Forecasting Oil and Gas Development Company Ltd. Share Prices Using Orange},
  howpublished = {EasyChair Preprint 3588},
  year      = {EasyChair, 2020}}
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