Miroslav Kubát

10.8k citations
97 papers · 6.5k indexed · 5 hit papers · h-index 23

Miroslav Kubát

90 papers receiving 6.1k citations

Hit Papers

Addressing the Curse of Imbalanced Training Sets: One-Sid...1996202620062016199719961998199620154008001.2k

Peers

Miroslav Kubát
Comparison fields: 5 of 204
  • Artificial Intelligence 4.4k
  • Information Systems 1.0k
  • Computer Vision and Pattern Recognition 821
  • Electrical and Electronic Engineering 726
  • Signal Processing 589
Replace Pedro Larrañaga with:
Pedro Larrañaga Spain
Charles X. Ling Canada
André C. P. L. F. de Carvalho Brazil
George H. John United States
Nebojša Bačanin Serbia
José A. Lozano Spain
Pádraig Cunningham Ireland
Bo Yang China
Alex A. Freitas United Kingdom
Qing He China
Miroslav Kubát relative to Pedro Larrañaga Spain Pedro Larrañaga's profile →
Citations per field
00.5×1.5×1.9×
Pedro Larrañaga · 1×
Citations per year

Countries citing papers authored by Miroslav Kubát

Since Specialization
Citations

This map shows the geographic impact of Miroslav Kubát's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miroslav Kubát with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miroslav Kubát more than expected).

Fields of papers citing papers by Miroslav Kubát

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miroslav Kubát. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miroslav Kubát. The network helps show where Miroslav Kubát may publish in the future.

Co-authorship network of co-authors of Miroslav Kubát

This figure shows the co-authorship network connecting the top 25 collaborators of Miroslav Kubát. A scholar is included among the top collaborators of Miroslav Kubát based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miroslav Kubát. Miroslav Kubát is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2
MeMO : Membership-Based Minority Oversampling for Class Balancing.
1
3
Time spent on a web page is sufficient to infer a user's interest
17
4
Association Mining in Gradually Changing Domains
3
5
Modifying Upstart for Use in Multiclass Numerical Domains
1
6
Should machines learn how to play games
0
7
Machines that learn to play games
36
8
Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes
5
9
Recycling decision trees in numeric domains
1
10
Voting Nearest-Neighbor Subclassifiers
15
11
Initializing RBF-networks with small subsets of training examples
2
12 1
13 173
14 81
15
Addressing the Curse of Imbalanced Training Sets: One-Sided Selection.breakdown →
1469
16
Second Tier for Decision Trees.
9
17
Adapting to Drift in Continuous Domains
10
18
Trimming the inputs of RBF networks.
2
19 5
20
Learning flexible concepts from streams of examples: FLORA2
15

About Miroslav Kubát

Miroslav Kubát is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics, having authored 97 papers that have together received 6.5k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (14 papers), Imbalanced Data Classification Techniques (13 papers) and Rough Sets and Fuzzy Logic (13 papers). The work is most often cited by research in Artificial Intelligence (4.4k citations), Signal Processing (589 citations) and Information Systems (1.0k citations). Miroslav Kubát has collaborated with scholars based in United States, Czechia and Austria. Frequent co-authors include Stan Matwin, Gerhard Widmer, Robert C. Holte, Nooshin Nabizadeh, Kanoksri Sarinnapakorn, Peerapon Vateekul, Johannes Fürnkranz, Kamal Premaratne, Gert Pfurtscheller and Doris Flotzinger. Their work appears in journals such as Expert Systems with Applications, Artificial Intelligence and IEEE Transactions on Knowledge and Data Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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