Geodesic
Determining fulfilment rate of public procurement contracts
Fundamentalʹnaâ i prikladnaâ matematika, Tome 25 (2024) no. 1, pp. 237-250.

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This paper investigates the problem of predicting the success of contracts concluded in Russia. It is based on a machine learning algorithm: a gradient binning over solver 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. 
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M. A. Khromov; A. V. Shokurov. Determining fulfilment rate of public procurement contracts. Fundamentalʹnaâ i prikladnaâ matematika, Tome 25 (2024) no. 1, pp. 237-250. http://geodesic.mathdoc.fr/item/FPM_2024_25_1_a13/

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