title: ÐÑÐ±Ð¾Ñ Ð¸ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ° Ð´Ð°Ð½Ð½ÑÑ Ð´Ð»Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð² Ð±Ð¸Ð·Ð½ÐµÑ-Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÐºÐµ
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: Selecting and preparing data for the use of machine learning algorithms in business intelligence
Creators: name: ÐÐ¸ ÐÑÐ¸Ð½
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: 2024
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¾Ð½Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
machine learning
data analysis
neural networks
correlation analysis
prediction

description: Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐµÑÐºÐ¾Ð³Ð¾, ÑÐ½Ð¸Ð²ÐµÑÑÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ðº Ð¾ÑÐ±Ð¾ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÑÐ°ÑÑÐµÐ¹ Ð²ÑÐ±Ð¾ÑÐºÐ¸ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð² Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ð¸ Ð½Ð° Ð¿ÑÐ°ÐºÑÐ¸ÐºÐµ Ð½Ð¾Ð²Ð¾Ð³Ð¾ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ¾Ð³Ð»Ð°ÑÐ¸Ñ Ð² Ð´Ð¸Ð½Ð°Ð¼Ð¸ÐºÐµ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐµÐ³Ð¾ÑÑ Ð¿ÑÐ¸ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ð¸ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°. ÐÑÐ»Ð¸ ÑÐµÑÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸: â ÑÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ð½Ð¾Ðµ Ð¿Ð¾Ð»Ðµ, Ð¾Ð¿Ð¸ÑÐ°ÑÑ Ð²Ð»Ð¸ÑÐ½Ð¸Ðµ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð², Ð²Ð¾Ð·Ð½Ð¸ÐºÐ°ÑÑÐ¸Ñ Ð² ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð½ÐµÐ¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²Ð»ÐµÐ½Ð½ÑÑ Ð¸Ð»Ð¸ Ð½ÐµÐ¿ÑÐ¾Ð²ÐµÑÐµÐ½Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¿ÑÐ¸ ÑÐµÑÐµÐ½Ð¸Ð¸ Ð·Ð°Ð´Ð°Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÐÐ; â Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°ÑÑ Ð²Ð°Ð¶Ð½Ð¾ÑÑÑ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ, Ð¾Ð¿Ð¸ÑÐ°ÑÑ Ð¿Ð¾Ð»Ð¾Ð¶Ð¸ÑÐµÐ»ÑÐ½ÑÐµ ÑÑÑÐµÐºÑÑ Ð¾Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐ½Ð¸Ð²ÐµÑÑÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ð¿Ð¾ Ð¿ÑÐµÐ´ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐµ Ð´Ð°Ð½Ð½ÑÑ; â Ð¾ÑÐµÐ½Ð¸ÑÑ ÑÑÐµÐ¿ÐµÐ½Ñ Ð¸Ð·ÑÑÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¿Ð¾ÑÑÐµÐ´ÑÑÐ²Ð¾Ð¼ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð½Ð°ÑÑÐ½ÑÑ ÑÐ°Ð±Ð¾Ñ Ð¿Ð¾ ÑÐµÐ¼Ð°ÑÐ¸ÐºÐµ; â Ð¿ÑÐ¾Ð²ÐµÑÑÐ¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ðº Ð¾ÑÐ±Ð¾ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÑÐ°ÑÑÐµÐ¹ Ð²ÑÐ±Ð¾ÑÐºÐ¸, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÑ Ð½Ð¾Ð²ÑÐ¹ Ð¼ÐµÑÐ°Ð½Ð¸Ð·Ð¼ Ð¾ÑÐµÐ½ÐºÐ¸ Ð²Ð·Ð°Ð¸Ð¼Ð¾ÑÐ²ÑÐ·ÐµÐ¹ Ð¼ÐµÐ¶Ð´Ñ Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐ¼Ð¸ ÑÑÐ´Ð°Ð¼Ð¸; â ÑÐ¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÐµÑÐµÐ½Ð¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐ¾Ð²Ð°ÑÐ½Ð¾Ð³Ð¾ ÑÐ¿ÑÐ¾ÑÐ° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¾Ð¿Ð¸ÑÐ°ÑÑÑ Ð½Ð° Ð¼ÐµÑÐ¾Ð´Ñ, Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð² ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ; â ÑÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°ÑÑ Ð²ÑÐ²Ð¾Ð´Ñ Ð¾ Ð´Ð°Ð»ÑÐ½ÐµÐ¹ÑÐµÐ¼ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ð¸ Ð¸Ð·ÑÑÐµÐ½Ð½Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð°. ÐÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½ Ð¿Ð¾Ð´ÑÐ¾Ð´ Ðº ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¾Ð±ÑÑÐ°ÑÑÐµÐ¹ Ð²ÑÐ±Ð¾ÑÐºÐ¸ Ð´Ð»Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð½Ð¾Ð²Ð¾Ð³Ð¾ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ° Ð¾ÑÐµÐ½ÐºÐ¸ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¾Ð½Ð½ÑÑ Ð²Ð·Ð°Ð¸Ð¼Ð¾ÑÐ²ÑÐ·ÐµÐ¹.
description: The aim of the work is to form a clear, universal approach to data selection and the formation of a training sample for solving problems using machine learning algorithms, as well as in the study and practical application of a new coefficient of agreement in dynamics used in correlation analysis. The following tasks were solved: to form a problem field, to describe the influence of factors arising from the use of unprepared or unverified data in solving problems using AI; to substantiate the importance of the problem, to describe the positive effects of applying a universal approach to data preparation; to assess the degree of study of the problem by analyzing scientific papers on the subject; to conduct a study of the approach to data selection and the formation of a training sample, as well as to explore a new mechanism for assessing the relationships between time series; to simulate the solution of the problem of forecasting commodity demand using machine learning algorithms, based on the methods obtained as a result of the study; to form conclusions about the further development of the studied approach. An approach to the formation of a high-quality training sample for machine learning is proposed, as well as the practical application of a new tool for evaluating correlation relationships.