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Isaiah’s Structure from Random Forest Regression Analysis

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  • Richard J. Butler

Abstract

This is the first paper to analyze the tripartite linguistic structure of Isaiah using Random Forest Regression, a supervised machine learning statistical approach. By predicting the occurrences of ‘judgment’ and ‘hope’ verses, we examine the threefold structure of Isaiah (section 1--chapters 1-39; section 2--chapters 40-55; and section 3--chapters 56-66) for differences in expression within and between each section. We find more inter-sectional homogeneity between sections 1 and 2 than between sections 1 and 3 or between sections 2 and 3, with respect to both judgment and hope word structures. Moreover, analysis of the judgment-vs-hope word structure indicate that section 3 heterogeneity differs significantly from sections 1 and 2 homogeneity, reinforcing the hypothesis that there is indeed a post-exilic authorship of section 3 (Isaiah 56-66).

Suggested Citation

  • Richard J. Butler, 2023. "Isaiah’s Structure from Random Forest Regression Analysis," Asian Culture and History, Canadian Center of Science and Education, vol. 15(1), pages 1-34, June.
    • Handle: RePEc:ibn:ach123:v:15:y:2023:i:1:p:34
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    1. Hassan Adamu & Syaheerah Lebai Lutfi & Nurul Hashimah Ahamed Hassain Malim & Rohail Hassan & Assunta Di Vaio & Ahmad Sufril Azlan Mohamed, 2021. "Framing Twitter Public Sentiment on Nigerian Government COVID-19 Palliatives Distribution Using Machine Learning," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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