D-Index & Metrics Best Publications
Computer Science
UK
2023

D-Index & Metrics 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.

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 67 Citations 17,570 346 World Ranking 1386 National Ranking 80

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in United Kingdom Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Artificial intelligence, Computer programming, Machine learning, Data mining and Genetic algorithm. The Artificial intelligence study combines topics in areas such as Perspective and Heuristics. The concepts of his Computer programming study are interwoven with issues in Preprocessor, Knowledge representation and reasoning, Association rule learning, Data stream mining and Data set.

His research integrates issues of Algorithm, Ant colony optimization algorithms and Knowledge extraction in his study of Machine learning. His Data mining research includes themes of Statistical classification, Genetic programming, Set and Ant colony. His Genetic algorithm study combines topics from a wide range of disciplines, such as Variable, Phenotype, Genotype, Facility location problem and Chromosome.

His most cited work include:

  • Data mining with an ant colony optimization algorithm (815 citations)
  • Data Mining and Knowledge Discovery with Evolutionary Algorithms (594 citations)
  • A survey of hierarchical classification across different application domains (553 citations)

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

Alex A. Freitas spends much of his time researching Artificial intelligence, Machine learning, Data mining, Computer programming and Genetic programming. His Artificial intelligence research integrates issues from Genetic algorithm and Pattern recognition. His Machine learning study incorporates themes from Algorithm and Ant colony optimization algorithms.

Class is closely connected to Set in his research, which is encompassed under the umbrella topic of Data mining. His study looks at the intersection of Computer programming and topics like Artificial immune system with Fuzzy rule. As part of the same scientific family, Alex A. Freitas usually focuses on Evolutionary algorithm, concentrating on Evolutionary computation and intersecting with Memetic algorithm.

He most often published in these fields:

  • Artificial intelligence (59.78%)
  • Machine learning (46.83%)
  • Data mining (35.54%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (59.78%)
  • Machine learning (46.83%)
  • Data mining (35.54%)

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

Alex A. Freitas mainly investigates Artificial intelligence, Machine learning, Data mining, Pattern recognition and Classifier. Artificial intelligence is a component of his Statistical classification, Feature selection, Class, Decision tree and Naive Bayes classifier studies. Evolutionary algorithm, Bayesian network, Multi-label classification, Genetic programming and Interpretability are the primary areas of interest in his Machine learning study.

Alex A. Freitas usually deals with Evolutionary algorithm and limits it to topics linked to Rule induction and Set. His Data mining study frequently draws connections to adjacent fields such as Longitudinal study. His Pattern recognition research is multidisciplinary, incorporating elements of Genetic algorithm and Probabilistic logic.

Between 2014 and 2021, his most popular works were:

  • A novel applicability domain technique for mapping predictive reliability across the chemical space of a QSAR: reliability-density neighbourhood (104 citations)
  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (82 citations)
  • An extensive evaluation of seven machine learning methods for rainfall prediction in weather derivatives (60 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Feature selection, Pattern recognition and Classifier. His work on Model organism expands to the thematically related Artificial intelligence. He focuses mostly in the field of Machine learning, narrowing it down to topics relating to Gene ontology and, in certain cases, Directed acyclic graph.

He combines subjects such as Neighbourhood, Molecular descriptor, Data mining and Naive Bayes classifier with his study of Feature selection. His Decision tree study in the realm of Data mining connects with subjects such as sort. Within one scientific family, Alex A. Freitas focuses on topics pertaining to Genetic algorithm under Pattern recognition, and may sometimes address concerns connected to Classifier chains.

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

Data mining with an ant colony optimization algorithm

R.S. Parpinelli;H.S. Lopes;A.A. Freitas.
IEEE Transactions on Evolutionary Computation (2002)

1393 Citations

Data Mining and Knowledge Discovery with Evolutionary Algorithms

Alex A. Freitas.
(2002)

1129 Citations

A survey of hierarchical classification across different application domains

Carlos N. Silla;Alex A. Freitas.
Data Mining and Knowledge Discovery (2011)

934 Citations

A Survey of Evolutionary Algorithms for Clustering

E.R. Hruschka;R.J.G.B. Campello;A.A. Freitas;A.C.P.L.F. de Carvalho.
systems man and cybernetics (2009)

830 Citations

A survey of evolutionary algorithms for data mining and knowledge discovery

Alex A. Freitas.
Advances in evolutionary computing (2003)

639 Citations

Comprehensible classification models: a position paper

Alex A. Freitas.
Sigkdd Explorations (2014)

551 Citations

On rule interestingness measures

A. A. Freitas.
Knowledge Based Systems (1999)

437 Citations

A Survey of Evolutionary Algorithms for Decision-Tree Induction

R. C. Barros;M. P. Basgalupp;A. C. P. L. F. de Carvalho;A. A. Freitas.
systems man and cybernetics (2012)

358 Citations

Mining Very Large Databases with Parallel Processing

Alex A. Freitas;S. H. Lavington.
(1997)

342 Citations

Discovering comprehensible classification rules with a genetic algorithm

M.V. Fidelis;H.S. Lopes;A.A. Freitas.
congress on evolutionary computation (2000)

287 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Alex A. Freitas

Sebastián Ventura

Sebastián Ventura

University of Córdoba

Publications: 66

Francisco Herrera

Francisco Herrera

University of Granada

Publications: 58

André C. P. L. F. de Carvalho

André C. P. L. F. de Carvalho

Universidade de São Paulo

Publications: 35

Jason H. Moore

Jason H. Moore

University of Pennsylvania

Publications: 35

Salvador García

Salvador García

University of Granada

Publications: 28

Jon Timmis

Jon Timmis

University of Sunderland

Publications: 24

Ashish Ghosh

Ashish Ghosh

Indian Statistical Institute

Publications: 21

Mengjie Zhang

Mengjie Zhang

Victoria University of Wellington

Publications: 19

Bart Baesens

Bart Baesens

KU Leuven

Publications: 18

Cynthia Rudin

Cynthia Rudin

Duke University

Publications: 17

Licheng Jiao

Licheng Jiao

Xidian University

Publications: 17

David Martens

David Martens

University of Antwerp

Publications: 16

Sašo Džeroski

Sašo Džeroski

Jožef Stefan Institute

Publications: 16

John F. Roddick

John F. Roddick

Flinders University

Publications: 16

João Pedro de Magalhães

João Pedro de Magalhães

University of Birmingham

Publications: 15

Ricardo J. G. B. Campello

Ricardo J. G. B. Campello

University of Newcastle Australia

Publications: 15

Trending Scientists

Evan G. Colgan

Evan G. Colgan

IBM (United States)

Christopher K. Ober

Christopher K. Ober

Cornell University

Sanzhong Luo

Sanzhong Luo

Tsinghua University

Bernard Riedl

Bernard Riedl

Université Laval

Xiangdong Ding

Xiangdong Ding

Xi'an Jiaotong University

Joan E. Bailey-Wilson

Joan E. Bailey-Wilson

National Institutes of Health

Craig D. Allen

Craig D. Allen

United States Geological Survey

Margaret E. McCully

Margaret E. McCully

Commonwealth Scientific and Industrial Research Organisation

Paul D. Lampe

Paul D. Lampe

Fred Hutchinson Cancer Research Center

Dennis S. Nielsen

Dennis S. Nielsen

University of Copenhagen

Thomas A. Richards

Thomas A. Richards

University of Oxford

Brian A. MacVicar

Brian A. MacVicar

University of British Columbia

Bryan E. Pfingst

Bryan E. Pfingst

University of Michigan–Ann Arbor

Linda J. Skitka

Linda J. Skitka

University of Illinois at Chicago

John Pernow

John Pernow

Karolinska University Hospital

Elissa S. Epel

Elissa S. Epel

University of California, San Francisco

Something went wrong. Please try again later.