title: ÐÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð²ÐµÐ±-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐµÐ³Ð¾ ÑÐ·ÑÐº R Ð¸ Ð¿Ð°ÐºÐµÑ Shiny.
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Prototype of an analytical application using the R language and the Shiny package
Creators: name: Ð¡Ð¸Ð·ÐµÐ²Ð°, ÐÐ°ÑÑÑ
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¸Ð½ÑÐµÐ»Ð»ÐµÐºÑÑÐ°Ð»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð´Ð°Ð½Ð½ÑÑ
shiny
Ð²ÐµÐ±-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐµÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
data mining
web application
cluster analysis
regression analysis

description: Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¿ÑÐ¾Ð²ÐµÑÑÐ¸ Ð°Ð½Ð°Ð»Ð¸Ð· Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ Ð¿Ð¾ ÑÑÐ½ÐºÑ Ð½ÐµÐ´Ð²Ð¸Ð¶Ð¸Ð¼Ð¾ÑÑÐ¸ Ð² Ð Ð¾ÑÑÐ¸Ð¸ Ð·Ð° 2021 Ð³Ð¾Ð´ Ð¸ Ñ ÐµÐ³Ð¾ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ¾Ð·Ð´Ð°ÑÑ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ Ð²ÐµÐ±-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Shiny, Ð² ÐºÐ¾ÑÐ¾ÑÐ¾Ð¼ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÑÑÑÑÑ Ð¿Ð¾Ð¸ÑÐº Ð¸ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð· ÑÐµÐ½Ñ ÐºÐ²Ð°ÑÑÐ¸Ñ Ð¿Ð¾ Ð²Ð²ÐµÐ´ÐµÐ½Ð½ÑÐ¼ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ°Ð¼, Ð²Ð¸Ð·ÑÐ°Ð»Ð¸Ð·Ð¸ÑÑÑÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿Ð¾Ð¸ÑÐºÐ° ÐºÐ²Ð°ÑÑÐ¸Ñ Ð² ÑÐ°Ð±Ð»Ð¸ÑÐ½Ð¾Ð¹ ÑÐ¾ÑÐ¼Ðµ Ð¸ Ð½Ð° ÐºÐ°ÑÑÐµ, Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÑÑÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÐºÐ»Ð°ÑÑÐµÑÐ½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð°.Â ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¾ ÑÑÐ½ÐºÐµ Ð½ÐµÐ´Ð²Ð¸Ð¶Ð¸Ð¼Ð¾ÑÑÐ¸ Ð² Ð Ð¾ÑÑÐ¸Ð¸ Ð·Ð° 2021 Ð³.Â ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¸ Ð·Ð°ÐºÐ¾Ð½Ð¾Ð¼ÐµÑÐ½Ð¾ÑÑÐ¸ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ, Ð¿ÑÐ¸ÑÑÑÐ¸Ðµ ÑÑÐ½ÐºÑ Ð½ÐµÐ´Ð²Ð¸Ð¶Ð¸Ð¼Ð¾ÑÑÐ¸ Ð² Ð Ð¾ÑÑÐ¸Ð¸ Ð² 2021 Ð³.Â ÐÐºÑÑÐ°Ð»ÑÐ½Ð¾ÑÑÑ ÑÐµÐ¼Ñ ÑÐ°Ð±Ð¾ÑÑ Ð¾Ð±ÑÑÐ»Ð¾Ð²Ð»ÐµÐ½Ð° ÑÐµÐ¼, ÑÑÐ¾ ÑÑÐ½Ð¾Ðº Ð½ÐµÐ´Ð²Ð¸Ð¶Ð¸Ð¼Ð¾ÑÑÐ¸ Ð² Ð Ð¾ÑÑÐ¸Ð¸ Ð¿ÑÐ¾Ð´Ð¾Ð»Ð¶Ð°ÐµÑ ÑÐ°ÑÑÐ¸ Ñ ÐºÐ°Ð¶Ð´ÑÐ¼ Ð³Ð¾Ð´Ð¾Ð¼. Ð­ÑÐ¾ Ð² ÑÐ²Ð¾Ñ Ð¾ÑÐµÑÐµÐ´Ñ ÑÑÐµÐ±ÑÐµÑ Ð´Ð°Ð»ÑÐ½ÐµÐ¸ÌÑÐµÐ³Ð¾ ÑÐ°Ð·Ð²Ð¸ÑÐ¸Ñ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¸Ì Ð¸ Ð²ÐµÐ±-ÑÐ°Ð¸ÌÑÐ¾Ð² Ñ ÑÐµÐ»ÑÑ Ð¿Ð¾Ð¸ÑÐºÐ° ÐºÐ²Ð°ÑÑÐ¸Ñ Ð´Ð»Ñ Ð¿Ð¾ÐºÑÐ¿ÐºÐ¸, Ð¿ÑÐ¾Ð´Ð°Ð¶Ð¸ Ð¸Ð»Ð¸ Ð°ÑÐµÐ½Ð´Ñ.Â Ð ÑÐ°Ð±Ð¾ÑÐµ Ð±ÑÐ» ÑÐ´ÐµÐ»Ð°Ð½ ÐºÑÐ°ÑÐºÐ¸Ð¸Ì Ð¾Ð±Ð·Ð¾Ñ ÑÐ·ÑÐºÐ° R Ð¸ ÐµÐ³Ð¾ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº Ð´Ð»Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿Ñ ÑÐ°Ð±Ð¾ÑÑ Ð¸Ð½ÑÐµÑÑÐµÐ¸ÌÑÐ½Ð¾Ð¸Ì Ð¸ ÑÐµÑÐ²ÐµÑÐ½Ð¾Ð¸Ì ÑÐ°ÑÑÐ¸ Ð²ÐµÐ±-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Shiny, Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÐºÐ»Ð°ÑÑÐµÑÐ½ÑÐ¸Ì Ð°Ð½Ð°Ð»Ð¸Ð· Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° k-means, Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° DBSCAN Ð¸ ÑÐ°ÑÑÑÐ¾ÑÐ½Ð¸Ð¸Ì ÐÐ¾Ð²ÐµÑÐ°. ÐÑÐ» Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÑÐµÐ³ÑÐµÑÑÐ¸Ð¾Ð½Ð½ÑÐ¸Ì Ð°Ð½Ð°Ð»Ð¸Ð· Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ°ÐºÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÐºÐ°Ðº Ð»Ð¸Ð½ÐµÐ¸ÌÐ½Ð°Ñ ÑÐµÐ³ÑÐµÑÑÐ¸Ñ, Ð´ÐµÑÐµÐ²ÑÑ ÑÐµÑÐµÐ½Ð¸Ð¸Ì. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð±ÑÐ»Ð¸ Ð²Ð¸Ð·ÑÐ°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ Ð¿Ð¾ÑÑÐµÐ´ÑÑÐ²Ð¾Ð¼ ÑÐ·ÑÐºÐ° R Ð¸ Ð¿Ð°ÐºÐµÑÐ° Shiny.
description: The theme of the graduation work is "A prototype of an analytical web application using the R language and the Shiny package". The purpose of the work is to analyze the dataset on the real estate market in Russia for 2021 and use it to create a prototype of the Shiny web application, which searches and predicts the price of apartments according to the entered parameters, visualizes the results of the search for apartments in tabular form and on a map, and demonstrates cluster analysis results. The object of the study is a set of data on the real estate market in Russia for 2021. The subject of the study is the features and patterns of development inherent in the real estate market in Russia in 2021. The relevance of the topic of the work is due to the fact that the real estate market in Russia continues to grow every year. This, in turn, requires further development of applications and websites in order to find apartments to buy, sell or rent. In the work, a brief overview of the R language and its libraries for machine learning was made, the principles of operation of the front-end and server parts of the Shiny web application were considered, cluster analysis was carried out using the k-means algorithm, the DBSCAN algorithm, and Gover distances. Regression analysis was carried out using such machine learning methods as linear regression, decision trees. The results obtained were visualized using the R language and the Shiny package.