Fuzzy Set-Based Isolation Forest
Paweł Karczmarek, Adam Kiersztyn, Witold Pedrycz
Abstract
One of the main challenges is the analysis of large data sets, in particular those containing various types of data, such as time, place, image, and those assuming categorical values. This type of data may contain numerous outliers. Despite the continuous development of data analysis, many methods can be effectively improved, in particular through the use of efficient solutions based on fuzzy set technologies. In this paper, we analyze the improvement of a well-known method, i.e. Isolation Forest, for which we introduce an innovative modification, referred to as the Fuzzy Set-Based Isolation Forest.
Topics & Concepts
Categorical variableOutlierData miningFuzzy setComputer scienceSet (abstract data type)Fuzzy logicIsolation (microbiology)Data setPattern recognition (psychology)Artificial intelligenceMachine learningProgramming languageMicrobiologyBiologyAnomaly Detection Techniques and ApplicationsTime Series Analysis and ForecastingNetwork Security and Intrusion Detection