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<p>This paper investigates the problem of predicting the success of contracts concluded in Russia. It is based on a&#xa0;machine learning algorithm: gradient boosting over decision trees. The classifier parameters are adjusted, and the most important features are generated and searched for. The following important attributes were found: percentage of contract price drop; contract price per day; contract price per employee; contract price multiplied by price change.</p>

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DETERMINING FULFILLMENT RATE OF PUBLIC PROCUREMENT CONTRACTS

  • 期刊论文

  • 发表日期：

    2026年1月1日

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  • M. K. Khromov,
  • A. V. Shokurov

摘要

This paper investigates the problem of predicting the success of contracts concluded in Russia. It is based on a machine learning algorithm: gradient boosting over decision trees. The classifier parameters are adjusted, and the most important features are generated and searched for. The following important attributes were found: percentage of contract price drop; contract price per day; contract price per employee; contract price multiplied by price change.