title: ÐÐ¾Ð¸ÑÐº Ð²ÑÐ±ÑÐ¾ÑÐ¾Ð² Ð² Ð¼Ð½Ð¾Ð³Ð¾Ð¼ÐµÑÐ½ÑÑ Ð´Ð°Ð½Ð½ÑÑ , Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½ÑÐ¹ Ð½Ð° SV-Ð¿Ð¾Ð´Ñ Ð¾Ð´Ðµ
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: Outlier Detection in Multidimensional Data Based on the SV Approach
Creators: name: ÐÑÐ¾ÐºÐ¾Ñ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: 2024
Subjects: Ð²ÑÐ±ÑÐ¾ÑÑ Ð² Ð¼Ð½Ð¾Ð³Ð¾Ð¼ÐµÑÐ½ÑÑ Ð´Ð°Ð½Ð½ÑÑ
ÑÐ°ÑÑÑÐ¾ÑÐ½Ð¸Ðµ ÐÐ°Ñ Ð°Ð»Ð°Ð½Ð¾Ð±Ð¸ÑÐ°
Ð¾Ð¿Ð¾ÑÐ½ÑÐµ Ð²ÐµÐºÑÐ¾ÑÑ
ÑÑÐµÐ½Ð¸ÑÐ¾Ð²Ð¾ÑÐ½Ð°Ñ Ð²ÑÐ±Ð¾ÑÐºÐ°
ÑÐµÑÑÐ¾Ð²Ð°Ñ Ð²ÑÐ±Ð¾ÑÐºÐ°
outliers
OneClass SVM
SVC
Mahalanobis distance
training set
test set

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description: This work examines methods for detecting outliers in multidimensional data. The main focus is on algorithms based on the SV approach â SVC and OneClass SVM. A comparison of the performance of these algorithms with the results of the method based on the Mahalanobis distance is presented. The tasks addressed during the research are: 1. Study of the selected outlier detection algorithms and their implementation. 2. Testing the implementation on model data and its validation on two types of real data. 3. Analysis of the results. Experiments were conducted in the paper to visually demonstrate how the parameters of the algorithms affect the efficiency of outlier detection. The analysis of the methods was carried out using software equipped with the necessary statistical functions and methods. The original codes implementing the algorithms were developed in the Google Colab environment using the Python programming language. Real datasets were sourced from open access. A comparative analysis of the performance of the three outlier detection algorithms was carried out based on the results obtained from numerical experiments. Methodological recommendations for using the algorithms to detect outliers in multidimensional data were developed. Based on the research conducted on real data, conclusions were drawn about the possibility of effectively applying the algorithms when analyzing multidimensional data of various natures.