Results 231 to 240 of about 88,867 (255)

Deterministic attribute selection for isolation forest

Pattern Recognition
Paweł Karczmarek, Łukasz Gałka
exaly   +3 more sources

A Novel Anomaly Score for Isolation Forests

2019
Isolation Forests represent a recent variant of Random Forests, specifically designed for one-class classification problems. In the original version, this method builds a set of extremely randomized trees to describe the set of points, subsequently measuring the “anomaly” of a testing point by looking at how much deep it arrives in each tree.
Mensi, Antonella, Bicego, Manuele
openaire   +3 more sources

An Alternative Exploitation of Isolation Forests for Outlier Detection

2021
Isolation Forests are one of the most successful outlier detection techniques: they isolate outliers by performing random splits in each node. It has been recently shown that a trained Random Forest-based model can also be used to define and extract informative distance measures between objects.
Antonella Mensi, Alessio Franzoni, David M. J. Tax, Manuele Bicego   +3 more
openaire   +3 more sources

Pollen dispersal and representation on an isolated, forested plateau*

New Phytologist, 1994
summaryModern pollen assemblages from 18 small ponds and wetlands on the spatially isolated and forested Kaibab Plateau were studied to determine how the pollen assemblages recorded vegetation patterns. Vegetation of the Plateau consists of an inner core of subalpine Picca/Abies forests, surrounded by mixed Abies/Picea/ Pseudotsuga/Pinus ponderosa ...
Stephen T, Jackson, Susan J, Smith
openaire   +2 more sources

Distribution Forest: An Anomaly Detection Method Based on Isolation Forest

2019
Anomaly detection refers to finding patterns in the data that do not meet expectations. Anomaly detection has a variety of application domains and scenarios, such as network intrusion detection, fraud detection and fault detection. This paper proposes a new anomaly detection method Distribution Forest (dForest) inspired by Isolation Forest (iForest ...
Chengfei Yao, Xiaoqing Ma, Biao Chen, Xiaosong Zhao, Gang Bai   +4 more
openaire   +1 more source

Sparse random projection isolation forest for outlier detection

Pattern Recognition Letters, 2022
Susanto Rahardja, Jiawei Yang, Xu Tan
exaly  

Interpretable Anomaly Detection with DIFFI: Depth-based feature importance of Isolation Forest

Engineering Applications of Artificial Intelligence, 2023
Gian Antonio Susto, Mattia Carletti
exaly  

On a Combination of Clustering Methods and Isolation Forest

2023
Michal Koziara, Pawel Karczmarek
openaire   +1 more source

Research on the fault monitoring method of marine diesel engines based on the manifold learning and isolation forest

Applied Ocean Research, 2021
Hui Chen, Wenfeng Gong, Cong Guan
exaly  

Decay detection of a marine gas turbine with contaminated data based on isolation forest approach

Ships and Offshore Structures, 2021
Jundong Zhang, Yejin Lin
exaly