A review of tree-based approaches for anomaly detection

T Barbariol, FD Chiara, D Marcato, GA Susto - Control charts and machine …, 2022‏ - Springer
Abstract Data-driven Anomaly Detection approaches have received increasing attention in
many application areas in the past few years as a tool to monitor complex systems in …

[HTML][HTML] Smart strawberry farming using edge computing and IoT

M Cruz, S Mafra, E Teixeira, F Figueiredo - Sensors, 2022‏ - mdpi.com
Strawberries are sensitive fruits that are afflicted by various pests and diseases. Therefore,
there is an intense use of agrochemicals and pesticides during production. Due to their …

Credal-based fuzzy number data clustering

Z Liu - Granular Computing, 2023‏ - Springer
It remains challenging in characterizing uncertain and imprecise information when clustering
fuzzy number data. To solve such a problem, this paper investigates a new credal-based …

[HTML][HTML] A probabilistic generalization of isolation forest

M Tokovarov, P Karczmarek - Information Sciences, 2022‏ - Elsevier
The problem of finding anomalies and outliers in datasets is one of the most important
challenges of modern data analysis. Among the commonly dedicated tools to solve this task …

A new method for fault detection of aero-engine based on isolation forest

H Wang, W Jiang, X Deng, J Geng - Measurement, 2021‏ - Elsevier
The research on fault detection of aero-engine is of great significance to its safe and reliable
operation. In this paper, a dynamic threshold method for aero-engine fault detection based …

Enhanced anomaly scores for isolation forests

A Mensi, M Bicego - Pattern Recognition, 2021‏ - Elsevier
Isolation Forest represents a variant of Random Forest largely and successfully employed
for outlier detection. The main idea is that outliers are likely to get isolated in a tree after few …

Fuzzy c-means-based isolation forest

P Karczmarek, A Kiersztyn, W Pedrycz… - Applied Soft …, 2021‏ - Elsevier
The problem of finding anomalies (outliers) in databases is one of the most important issues
in modern data analysis. One of the reasons is the occurrence of this issue in almost every …

Detection and classification of anomalies in large datasets on the basis of information granules

A Kiersztyn, P Karczmarek, K Kiersztyn… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Anomaly (outlier) detection is one of the most important problems of modern data analysis.
The sources of anomalies are varying. They can be the results of database users' mistakes …

A novel anomaly score based on kernel density fluctuation factor for improving the local and clustered anomalies detection of isolation forests

N Dong, B Ren, H Li, X Zhong, X Gong, J Han, J Lv… - Information …, 2023‏ - Elsevier
Isolation Forests (IF) and improved algorithms about anomaly scores are commonly used to
detect global, local, or clustered anomalies. However, these algorithms are limited in …

Isolation forest based on minimal spanning tree

Ł Gałka, P Karczmarek, M Tokovarov - IEEE Access, 2022‏ - ieeexplore.ieee.org
Detecting anomalies in data sets has been one of the most studied issues in modern data
analysis. Therefore, there is a plethora of applications in a very wide range of fields of …