Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jacek Koronacki"'
Autor:
Michał Dramiński, Jacek Koronacki
Publikováno v:
Journal of Statistical Software, Vol 85, Iss 1, Pp 1-28 (2018)
We describe the R package rmcfs that implements an algorithm for ranking features from high dimensional data according to their importance for a given supervised classification task. The ranking is performed prior to addressing the classification tas
Externí odkaz:
https://doaj.org/article/a8b7e3f9c1cb486bbf56e034eeaf995e
Autor:
Jacek Koronacki, Michał Dramiński
Publikováno v:
Journal of Statistical Software; Vol 85 (2018); 1-28
Journal of Statistical Software, Vol 85, Iss 1, Pp 1-28 (2018)
Journal of Statistical Software, Vol 85, Iss 1, Pp 1-28 (2018)
We describe the R package rmcfs that implements an algorithm for ranking features from high dimensional data according to their importance for a given supervised classification task. The ranking is performed prior to addressing the classification tas
Publikováno v:
Applied Mathematics and Computation. 256:591-601
There are numerous measures designed to evaluate quality of a given data grouping in terms of its distinctness and between-cluster separation. However, there seems to be no efficient method to assess distinctness of the intrinsic structure within dat
Autor:
Jan Komorowski, Jakub Mieczkowski, Marcin Kruczyk, Nicholas Baltzer, Michał Dramiński, Jacek Koronacki
Publikováno v:
Fundamenta Informaticae. 127:273-288
An important step prior to constructing a classifier for a very large data set is feature selection. With many problems it is possible to find a subset of attributes that have the same discriminative power as the full data set. There are many feature
Publikováno v:
Studies in Big Data ISBN: 9783319269870
The availability of very large data sets in Life Sciences provided earlier by the technological breakthroughs such as microarrays and more recently by various forms of sequencing has created both challenges in analyzing these data as well as new oppo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec2844b78965518909f3b1eef1f95da3
https://doi.org/10.1007/978-3-319-26989-4_12
https://doi.org/10.1007/978-3-319-26989-4_12
Publikováno v:
Advances in Machine Learning II ISBN: 9783642051784
Advances in Machine Learning II
Advances in Machine Learning II
Applications of machine learning techniques in Life Sciences are the main applications forcing a paradigm shift in the way these techniques are used. Rather than obtaining the best possible supervised classifier, the Life Scientist needs to know whic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a67205f033d5dab9f616ebc5d747fe5
https://doi.org/10.1007/978-3-642-05179-1_17
https://doi.org/10.1007/978-3-642-05179-1_17
Publikováno v:
Bioinformatics and Biology Insights, Vol 4 (2010)
Bioinformatics and Biology Insights, Vol 2010, Iss 4, Pp 137-146 (2010)
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights, Vol 2010, Iss 4, Pp 137-146 (2010)
Bioinformatics and Biology Insights
Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral
Autor:
Jan Komorowski, Alvaro Rada-Iglesias, Stefan Enroth, Claes Wadelius, Michał Dramiński, Jacek Koronacki
Publikováno v:
Bioinformatics (Oxford, England). 24(1)
Motivation: Pre-selection of informative features for supervised classification is a crucial, albeit delicate, task. It is desirable that feature selection provides the features that contribute most to the classification task per se and which should
Autor:
Michał Dramiński, Jacek Koronacki, Marcin Kierczak, Witold R. Rudnicki, Krzysztof Ginalski, Jan Komorowski
Publikováno v:
ResearcherID
Bioinformatics and Biology Insights, Vol 2009, Iss 3, Pp 109-127 (2009)
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights, Vol 3 (2009)
Bioinformatics and Biology Insights, Vol 2009, Iss 3, Pp 109-127 (2009)
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights, Vol 3 (2009)
Reverse transcriptase (RT) is a viral enzyme crucial for HIV-1 replication. Currently, 12 drugs are targeted against the RT. The low fidelity of the RT-mediated transcription leads to the quick accumulation of drug-resistance mutations. The sequence-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bdb64d8cbddc1cbe4ab1d503d5ac717d
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=MEDLINE&KeyUT=MEDLINE:20140064&KeyUID=MEDLINE:20140064
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=MEDLINE&KeyUT=MEDLINE:20140064&KeyUID=MEDLINE:20140064