D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 46 Citations 38,347 169 World Ranking 3453 National Ranking 7

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Bernhard Pfahringer mostly deals with Artificial intelligence, Machine learning, Data mining, Data stream mining and Software. Bernhard Pfahringer focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Pattern recognition and, in some cases, Scheme, Pruning, Probability density function and Process. As part of the same scientific family, Bernhard Pfahringer usually focuses on Machine learning, concentrating on Classifier and intersecting with Data analysis.

His study in Data mining is interdisciplinary in nature, drawing from both Ensemble learning, Boosting and Experimental data. His research brings together the fields of World Wide Web and Software. His World Wide Web course of study focuses on Data mining software and Multinomial naive bayes.

His most cited work include:

  • The WEKA data mining software: an update (15684 citations)
  • Classifier chains for multi-label classification (1233 citations)
  • MOA: Massive Online Analysis (1030 citations)

What are the main themes of his work throughout his whole career to date?

Bernhard Pfahringer focuses on Artificial intelligence, Machine learning, Data mining, Data stream mining and Data stream. His research integrates issues of Natural language processing and Pattern recognition in his study of Artificial intelligence. His is doing research in Ensemble learning, Decision tree, Semi-supervised learning, Boosting and Support vector machine, both of which are found in Machine learning.

In his study, which falls under the umbrella issue of Data mining, Multi-label classification is strongly linked to Scalability. His Data stream mining research integrates issues from Change detection and Software. His research links Data modeling with Concept drift.

He most often published in these fields:

  • Artificial intelligence (58.52%)
  • Machine learning (47.60%)
  • Data mining (27.95%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (58.52%)
  • Machine learning (47.60%)
  • Data stream mining (27.07%)

In recent papers he was focusing on the following fields of study:

Artificial intelligence, Machine learning, Data stream mining, Concept drift and Data mining are his primary areas of study. His work deals with themes such as Data stream and Natural language processing, which intersect with Artificial intelligence. Machine learning is represented through his Artificial neural network, Semi-supervised learning, Ensemble learning, Decision tree and Feature research.

The study incorporates disciplines such as Classifier, Naive Bayes classifier, Regression, Ensemble forecasting and Data science in addition to Data stream mining. His Concept drift research is multidisciplinary, relying on both Data modeling, Boosting and Feature selection. The various areas that Bernhard Pfahringer examines in his Data mining study include Projection, Cluster analysis, k-nearest neighbors algorithm, Disjoint sets and Dimensionality reduction.

Between 2017 and 2021, his most popular works were:

  • Regularisation of Neural Networks by Enforcing Lipschitz Continuity (101 citations)
  • Machine Learning for Data Streams: With Practical Examples in Moa (89 citations)
  • The online performance estimation framework: heterogeneous ensemble learning for data streams (46 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

The WEKA data mining software: an update

Mark Hall;Eibe Frank;Geoffrey Holmes;Bernhard Pfahringer.
Sigkdd Explorations (2009)

21919 Citations

MOA: Massive Online Analysis, a framework for stream classification and clustering.

Albert Bifet;Geoffrey Holmes;Bernhard Pfahringer;Philipp Kranen.
Proceedings of the First Workshop on Applications of Pattern Analysis (2010)

1691 Citations

Classifier chains for multi-label classification

Jesse Read;Bernhard Pfahringer;Geoff Holmes;Eibe Frank.
Machine Learning (2011)

1534 Citations

MOA: Massive Online Analysis

Albert Bifet;Geoff Holmes;Richard Kirkby;Bernhard Pfahringer.
Journal of Machine Learning Research (2010)

1073 Citations

New ensemble methods for evolving data streams

Albert Bifet;Geoff Holmes;Bernhard Pfahringer;Richard Kirkby.
knowledge discovery and data mining (2009)

665 Citations

Weka-A Machine Learning Workbench for Data Mining

Eibe Frank;Mark A. Hall;Geoffrey Holmes;Richard Kirkby.
The Data Mining and Knowledge Discovery Handbook (2009)

532 Citations

Meta-Learning by Landmarking Various Learning Algorithms

Bernhard Pfahringer;Hilan Bensusan;Christophe G. Giraud-Carrier.
international conference on machine learning (2000)

463 Citations

Multi-label Classification Using Ensembles of Pruned Sets

J. Read;B. Pfahringer;G. Holmes.
international conference on data mining (2008)

438 Citations

Multinomial naive bayes for text categorization revisited

Ashraf M. Kibriya;Eibe Frank;Bernhard Pfahringer;Geoffrey Holmes.
australasian joint conference on artificial intelligence (2004)

422 Citations

Locally weighted naive bayes

Eibe Frank;Mark Hall;Bernhard Pfahringer.
uncertainty in artificial intelligence (2002)

404 Citations

Best Scientists Citing Bernhard Pfahringer

Björn Schuller

Björn Schuller

Imperial College London

Publications: 100

Mengjie Zhang

Mengjie Zhang

Victoria University of Wellington

Publications: 72

Albert Bifet

Albert Bifet

University of Waikato

Publications: 65

João Gama

João Gama

University of Porto

Publications: 62

Francisco Herrera

Francisco Herrera

University of Granada

Publications: 60

André C. P. L. F. de Carvalho

André C. P. L. F. de Carvalho

Universidade de São Paulo

Publications: 57

Sebastián Ventura

Sebastián Ventura

University of Córdoba

Publications: 51

Edwin Lughofer

Edwin Lughofer

Johannes Kepler University of Linz

Publications: 48

Stefan Kramer

Stefan Kramer

Johannes Gutenberg University of Mainz

Publications: 47

Johannes Fürnkranz

Johannes Fürnkranz

Johannes Kepler University of Linz

Publications: 46

Bing Xue

Bing Xue

Victoria University of Wellington

Publications: 45

Lior Rokach

Lior Rokach

Ben-Gurion University of the Negev

Publications: 44

Iryna Gurevych

Iryna Gurevych

University of Paderborn

Publications: 42

Latifur Khan

Latifur Khan

The University of Texas at Dallas

Publications: 41

Eyke Hüllermeier

Eyke Hüllermeier

Ludwig-Maximilians-Universität München

Publications: 41

Taghi M. Khoshgoftaar

Taghi M. Khoshgoftaar

Florida Atlantic University

Publications: 41

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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