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Прогнозирование результатов ÑÐ¿Ð¾Ñ€Ñ‚Ð¸Ð²Ð½Ñ‹Ñ Ð¼Ð°Ñ‚Ñ‡ÐµÐ¹ методами машинного обучения

магистерская диссертация
descriptionPublicationkeyboard_double_arrow_right Other literature type 01 Jan 2017 Russian Publisher:Санкт-Петербургский политехнический университет Петра Великого

doi: 10.18720/spbpu/2/v17-6548

Прогнозирование результатов ÑÐ¿Ð¾Ñ€Ñ‚Ð¸Ð²Ð½Ñ‹Ñ Ð¼Ð°Ñ‚Ñ‡ÐµÐ¹ методами машинного обучения

Abstract

Ð’ данной работе рассматривается проблема прогнозирования результатов на примере Ð±Ð°ÑÐºÐµÑ‚Ð±Ð¾Ð»ÑŒÐ½Ñ‹Ñ Ð¼Ð°Ñ‚Ñ‡ÐµÐ¹ в американской Национальной ассоциации студенческого спорта NCAA. Реализована модель на основе алгоритма машинного обучения случайного леса Ñ€ÐµÑˆÐ°ÑŽÑ‰Ð¸Ñ Ð´ÐµÑ€ÐµÐ²ÑŒÐµÐ². Результаты сопоставлены с работами Ð·Ð°Ñ€ÑƒÐ±ÐµÐ¶Ð½Ñ‹Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ñ‚ÐµÐ»ÐµÐ¹, предложены и реализованы пути развития модели за счет добавления Ð·Ð½Ð°Ñ‡Ð¸Ð¼Ñ‹Ñ Ð¿Ñ€Ð¸Ð·Ð½Ð°ÐºÐ¾Ð². Итоговая модель имеет точность предсказания 78.35% для регулярного чемпионата и 77,18% для стадии плей-офф с функцией Ð»Ð¾Ð³Ð°Ñ€Ð¸Ñ„Ð¼Ð¸Ñ‡ÐµÑÐºÐ¸Ñ Ð¿Ð¾Ñ‚ÐµÑ€ÑŒ 0.470653.

Keywords

Научно-Ñ‚ÐµÑ Ð½Ð¸Ñ‡ÐµÑÐºÐ¾Ðµ прогнозирование, Кибернетические системы обучающие, логистическая регрессия, машинное обучение, результаты матчей

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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