UB Paderborn / Katalog / Suche / in CDI

An instance-weighting method to induce cost-sensitive trees

IEEE transactions on knowledge and data engineering, 2002-05, Vol.14 (3), p.659-665

Ting, Kai Ming

2002

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Classification Under Streaming Emerging New Classes: A Solution Using Completely-Random Trees

IEEE transactions on knowledge and data engineering, 2017-08, Vol.29 (8), p.1605-1618

2017

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Isolation-Based Anomaly Detection

ACM transactions on knowledge discovery from data, 2012-03, Vol.6 (1), p.1-39

2012

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A general stochastic clustering method for automatic cluster discovery

Pattern recognition, 2011-10, Vol.44 (10), p.2786-2799

2011

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Feature-subspace aggregating: ensembles for stable and unstable learners

Machine learning, 2011-03, Vol.82 (3), p.375-397

2011

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Isolation‐based anomaly detection using nearest‐neighbor ensembles

Computational intelligence, 2018-11, Vol.34 (4), p.968-998

2018

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Local contrast as an effective means to robust clustering against varying densities

Machine learning, 2018-09, Vol.107 (8-10), p.1621-1645

2018

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Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems

Machine learning, 2016-11, Vol.105 (2), p.301-304

2016

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Isolation Distributional Kernel A New Tool for Point & Group Anomaly Detection

IEEE transactions on knowledge and data engineering, 2021, p.1-1

2021

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Half-space mass: a maximally robust and efficient data depth method

Machine learning, 2015-09, Vol.100 (2-3), p.677-699

2015

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Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

Machine learning, 2012-02, Vol.86 (2), p.233-272

2012

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LiNearN: A new approach to nearest neighbour density estimator

Pattern recognition, 2014-08, Vol.47 (8), p.2702-2720

2014

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Mass estimation

Machine learning, 2013, Vol.90 (1), p.127-160

2013

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On Detecting Clustered Anomalies Using SCiForest

Machine Learning and Knowledge Discovery in Databases, p.274-290

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Music classification via the bag-of-features approach

Pattern recognition letters, 2011-10, Vol.32 (14), p.1768-1777

2011

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Learning Sparse Kernel Classifiers for Multi-Instance Classification

IEEE transaction on neural networks and learning systems, 2013-09, Vol.24 (9), p.1377-1389

2013

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Relevance feature mapping for content-based multimedia information retrieval

Pattern recognition, 2012-04, Vol.45 (4), p.1707-1720

2012

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On the application of ROC analysis to predict classification performance under varying class distributions

Machine learning, 2005, Vol.58 (1), p.25-32

2005

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z-SVM: An SVM for Improved Classification of Imbalanced Data

AI 2006: Advances in Artificial Intelligence, 2006, Vol.4304, p.264-273

2006

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Kernel-based clustering via Isolation Distributional Kernel

Information systems (Oxford), 2023-07, Vol.117, p.102212, Article 102212

2023

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Density-ratio based clustering for discovering clusters with varying densities

Pattern recognition, 2016-12, Vol.60, p.983-997

2016

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Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel

The Journal of artificial intelligence research, 2021, Vol.71, p.667-695

2021

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Isolation Forest

2008 Eighth IEEE International Conference on Data Mining, 2008, p.413-422

2008

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Classifying under computational resource constraints : anytime classification using probabilistic estimators

Machine learning, 2007-10, Vol.69 (1), p.35-53

2007

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New Class Adaptation Via Instance Generation in One-Pass Class Incremental Learning

2017 IEEE International Conference on Data Mining (ICDM), 2017, p.1207-1212

2017

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An instance-weighting method to induce cost-sensitive trees

Classification Under Streaming Emerging New Classes: A Solution Using Completely-Random Trees

Isolation-Based Anomaly Detection

A general stochastic clustering method for automatic cluster discovery

Feature-subspace aggregating: ensembles for stable and unstable learners

Isolation‐based anomaly detection using nearest‐neighbor ensembles

Local contrast as an effective means to robust clustering against varying densities

Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems

Isolation Distributional Kernel A New Tool for Point & Group Anomaly Detection

Half-space mass: a maximally robust and efficient data depth method

Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

LiNearN: A new approach to nearest neighbour density estimator

Mass estimation

On Detecting Clustered Anomalies Using SCiForest

Music classification via the bag-of-features approach

Learning Sparse Kernel Classifiers for Multi-Instance Classification

Relevance feature mapping for content-based multimedia information retrieval

On the application of ROC analysis to predict classification performance under varying class distributions

z-SVM: An SVM for Improved Classification of Imbalanced Data

Kernel-based clustering via Isolation Distributional Kernel

Density-ratio based clustering for discovering clusters with varying densities

Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel

Isolation Forest

Classifying under computational resource constraints : anytime classification using probabilistic estimators

New Class Adaptation Via Instance Generation in One-Pass Class Incremental Learning

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