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Titlebook: Identifying the Complex Causes of Civil War; A Machine Learning A Atin Basuchoudhary,James T. Bang,Tinni Sen Book 2021 The Editor(s) (if ap

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發(fā)表于 2025-3-26 23:04:32 | 只看該作者
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發(fā)表于 2025-3-27 03:17:30 | 只看該作者
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發(fā)表于 2025-3-27 06:24:23 | 只看該作者
Epilogue,This chapter summarizes the main findings of the book.
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發(fā)表于 2025-3-27 11:16:52 | 只看該作者
Data Description and Preliminary Processing,th insufficient data and then explain the process of imputing missing values in the remaining data set. Finally, we describe the process of Recursive Feature Elimination that results in the optimal number of variables that predict civil conflict.
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發(fā)表于 2025-3-27 13:44:58 | 只看該作者
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發(fā)表于 2025-3-27 20:09:02 | 只看該作者
https://doi.org/10.1007/978-3-030-81993-4machine learning; conflict studies; artificial intelligence; economic variables; demographic variables; c
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發(fā)表于 2025-3-28 01:40:17 | 只看該作者
Book 2021causal pathways that cause civil conflict over others, thus teasing out the complex interrelationships between the most important variables that cause civil conflict. Success in this realm will lead to scientific theories of conflict that will be useful in preventing and ending civil conflict. After
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發(fā)表于 2025-3-28 04:16:08 | 只看該作者
39#
發(fā)表于 2025-3-28 07:07:23 | 只看該作者
Infant Mortality, State Capacity, Rents, and Civil War,st that traditional parametric empirical techniques can be misleading and have dangerous policy implications. To be precise, we show that increased government consumption expenditures can increase conflict in some variable ranges, even if the average effect is to reduce conflict.
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