A Novel Feature Selection and Short-Term Price Forecasting Based on a Decision Tree (J48) Model

Ankit Kumar Srivastava, Devender Singh, Ajay Shekhar Pandey and Tarun Maini
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Ankit Kumar Srivastava: Electrical Engineering Department, Institute of Engineering & Technology, Dr. Rammanohar Lohia Avadh University, Ayodhya 224001, India
Devender Singh: Electrical Engineering Department, Indian Institute of Technology (BHU), Varanasi 221005, India
Ajay Shekhar Pandey: Electrical Engineering Department, Kamla Nehru Institute of Technology, Sultanpur 228118, India
Tarun Maini: Electrical Engineering Department, Indian Institute of Technology (BHU), Varanasi 221005, India

Energies, 2019, vol. 12, issue 19, 1-17

Abstract: A novel feature selection method based on a decision tree (J48) for price forecasting is proposed in this work. The method uses a genetic algorithm along with a decision tree classifier to obtain the minimum number of features giving an optimum forecast accuracy. The usefulness of the proposed approach is established through the performance test of the forecaster using the feature selected by this approach. It is found that the forecast with the selected feature consistently out-performed than that having larger feature set.

Keywords: price forecasting; J48 classifier; feature selection; elite genetic algorithm; confidence interval (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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