Comparative analysis of machine learning methods for forecasting industry indicators of the Russian Federation

被引：0
|
作者：
Kitova, O., V [1 ]
Savinova, V. M. [1 ]
Iksanov, V. R. [1 ]
机构：
[1] Plekhanov Russian Univ Econ, Moscow, Russia
来源：
VOPROSY ISTORII | 2022年 / 9卷 / 02期
关键词：
prediction; model; multiple linear regression; support vector machine; regression decision tree; neural network; nearest neighbor method;
D O I：
10.31166/VoprosyIstorii202209Statyi37
中图分类号：
K [历史、地理];
学科分类号：
06 ;
摘要：
At the moment, the problem of forecasting is becoming more and more relevant. The unstable economic and political situation leads to the fact that in order to make high-quality and timely decisions, it is necessary to obtain reliable forecasts. In this regard, economic forecasting tools are actively developing. Within the framework of this study, indicators of the sphere of industrial production were considered.
引用
收藏
页码：248 / 262
页数：15
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