title: XGBOOST: ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: XGBOOST: classification of parameters of regression analysis methods
Creators: name: Ð§ÐµÐ¿ÑÐ»Ð¸Ñ, ÐÐ¸ÑÐ°Ð¸Ð»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: Ð ÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
Ð ÑÐ´Ñ (Ð¼Ð°Ñ.) Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ
ÐºÑÑÐ¾ÑÐ½Ð¾-Ð¿Ð¾Ð»Ð¸Ð½Ð¾Ð¼Ð¸Ð°Ð»ÑÐ½Ð°Ñ ÑÐµÐ³ÑÐµÑÑÐ¸Ñ
Ð¼Ð¾Ð¼ÐµÐ½ÑÑ ÑÑÑÑÐºÑÑÑÐ½Ð¾Ð³Ð¾ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸
piecewise polynomial regression
moments of model structural change

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: XGBOOST: ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°. ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ PW-ÑÑÑÐ¸Ð¼Ð°ÑÐ¾Ñ â Ð¾Ð´Ð¸Ð½ Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾ÑÐµÐ½ÐºÐ¸ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÐºÑÑÐ¾ÑÐ½Ð¾-Ð¿Ð¾Ð»Ð¸Ð½Ð¾Ð¼Ð¸Ð°Ð»ÑÐ½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð´Ð»Ñ Ð½ÐµÑÑÐ°ÑÐ¸Ð¾Ð½Ð°ÑÐ½ÑÑ Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ ÑÑÐ´Ð¾Ð², ÑÐ¾ÑÐ½ÐµÐµ, Ð¾Ð´Ð¸Ð½ Ð¸Ð· ÐµÐ³Ð¾ Ð³Ð¸Ð¿ÐµÑÐ¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² â Ð¼Ð¸Ð½Ð¸Ð¼Ð°Ð»ÑÐ½ÑÐ¹ ÑÐ°Ð·Ð¼ÐµÑ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ° Ð¿ÐµÑÐµÐ´ ÑÐ¾ÑÐºÐ¾Ð¹ ÑÐ°Ð·Ð»Ð°Ð´ÐºÐ¸. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ ÑÑÑÐ¸Ð¼Ð°ÑÐ¾ÑÐ° ÑÐ¾Ð´ÐµÑÐ¶Ð¸ÑÑÑ Ð²Ð¾ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐµ Ð. Ð. ÐÐ²Ð°Ð½ÐºÐ¾Ð²Ð° [8]. ÐÐ»Ñ ÑÑÐ¾Ð³Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐµ Ð¼Ð¾Ð´ÑÐ»Ð¸ ÑÑÐµÐ¹Ð¼Ð²Ð¾ÑÐºÐ° Ð´Ð»Ñ ÑÐµÐ´Ð°ÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ¾Ð½ÑÐ¸Ð³ÑÑÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐ°Ð¹Ð»Ð¾Ð² Ð¸ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð½Ð¾Ð¶ÐµÑÑÐ²Ð° Ð¾ÑÐµÐ½Ð¾Ðº ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿Ð¾ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐ¼ Ð¼ÐµÑÑÐ¸ÐºÐ°Ð¼; ÑÐ¾Ð±ÑÐ°Ð½Ð° (Ñ Ð¸ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸ÑÐ¼Ð¸) Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ° XGBoost, Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ð¸ ÐºÐ¾ÑÐ¾ÑÐ¾Ð¹ Ð±ÑÐ» ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¼Ð¾Ð´ÑÐ»Ñ Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð³Ð¸Ð¿ÐµÑÐ¿Ð°ÑÐ°Ð¼ÐµÑÑÐ° Ð¼ÐµÑÐ¾Ð´Ð° ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°Ð½ÑÑ Ð´Ð°ÑÑ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÑ Ð²ÑÐ´Ð²Ð¸Ð½ÑÑÑ ÑÑÐ´ Ð³Ð¸Ð¿Ð¾ÑÐµÐ· Ð¾ Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ð¸ Ð¾ÑÐµÐ½Ð¾Ðº ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸ Ð·Ð°Ð²Ð¸ÑÐ¸Ð¼Ð¾ÑÑÑÑ Ð¼ÐµÐ¶Ð´Ñ Ð¾ÑÐµÐ½ÐºÐ°Ð¼Ð¸ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¸ Ð·Ð½Ð°ÑÐµÐ½Ð¸ÐµÐ¼ Ð³Ð¸Ð¿ÐµÑÐ¿Ð°ÑÐ°Ð¼Ð¼ÐµÑÑÐ°.
description: The subject of graduate qualification work is XGBOOST: classification of parameters of regression analysis methods. The object of study in this thesis is the PW-estimator, one of the methods for estimating the parameters of a piecewise polynomial model for non-stationary time series. The study is aimed on its hypermarapeter, the minimum size of segment before break point. The A.A. Ivankov`s framework [8] contain the implementation of this estimator. There are software modules of this framework have been developed for editing configuration files and generating a set of quality evaluation for various metrics; compiled (with fixes) the XGBoost library, on the basis of which a software modules was implemented for classification of the hyperparameter of the regression analysis method. The results obtained make it possible to put forward a number if hypotheses about the behavior of the regression analysis quality estimates and the dependencies between the quality estimates and the value of the hyperparameter.