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The use of Score Functions of Distribution for Description of Parametric Families
Fabián, Zdeněk
2014 - anglický
Klíčová slova:
systems of distributions; Johnson transformations; score function of distribution; parametric families
Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd.
The use of Score Functions of Distribution for Description of Parametric Families
Robust Regularized Cluster Analysis for High-Dimensional Data
Kalina, Jan; Vlčková, Katarína
2014 - anglický
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for categorical data with a large number of categories. It exploits a regularized version of various test statistics of homogeneity in contingency tables as the measure of distance between two clusters. Further, our aim is cluster analysis of continuous data with a large number of variables. Various regularization techniques tailor-made for high-dimensional data have been proposed, which have however turned out to suffer from a high sensitivity to the presence of outlying measurements in the data. As a robust solution, we recommend to combine two newly proposed methods, namely a regularized version of robust principal component analysis and a regularized Mahalanobis distance, which is based on an asymptotically optimal regularization of the covariance matrix. We bring arguments in favor of the newly proposed methods.
Klíčová slova:
cluster analysis; robust data mining; big data; regularization
Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR.
Robust Regularized Cluster Analysis for High-Dimensional Data
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for ...
ITAT 2014. Information Technologies - Applications and Theory. Part II
Kůrková, Věra; Bajer, Lukáš; Peška, L.; Vojtáš, P.; Holeňa, Martin; Nehéz, M.
2014 - anglický
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague : Institute of Computer Science AS CR, 2014. 145 p. ISBN 978-80-87136-19-5. This volume is the second part of the two-volume proceedings of the 14th conference Information Technologies – Applications and Theory (ITAT 2014), which was held in Jasná, Demänovská Dolina, Slovakia, on September 25–29, 2014. ITAT is a computer science conference with the primary goal of exchanging information on recent research results. Overall, 51 papers were submitted to all conference tracks. This volume presents papers from the workshops and an extended abstract of a poster. Three specialized workshops were held as a part of the conference: Data Mining and Preference Learning on Web, Computational Intelligence and Data Mining, and Algorithmic Aspects of Complex Networks Analysis.
Klíčová slova:
computer science; machine-learning; computer linguistics; data-mining; bio-informatics; parallel processing
Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd.
ITAT 2014. Information Technologies - Applications and Theory. Part II
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague : Institute of Computer Science AS CR, 2014. 145 p. ISBN 978-80-87136-19-5. This volume is the second part of the ...
Description of Continuous Distributions and Data Samples by Means of Score Functions of Distribution
Fabián, Zdeněk
2014 - anglický
Klíčová slova:
score function; score mean; score variance; generalized Fisher information; data characteristics
Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd.
Description of Continuous Distributions and Data Samples by Means of Score Functions of Distribution
On the Consistency of an Estimator for Hierarchical Archimedean Copulas
Górecki, J.; Hofert, M.; Holeňa, Martin
2014 - anglický
The paper addresses an estimation procedure for hierarchical Archimedean copulas, which has been proposed in the literature. It is shown here that this estimation is not consistent in general. Furthermore, a correction is proposed, which leads to a consistent estimator.
Klíčová slova:
hierarchical Archimedean copula; Kendall distribution function; parameter estimation; structure determination; consistency
Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd.
On the Consistency of an Estimator for Hierarchical Archimedean Copulas
The paper addresses an estimation procedure for hierarchical Archimedean copulas, which has been proposed in the literature. It is shown here that this estimation is not consistent in general. ...
Robust Template Matching
Kalina, Jan
2013 - anglický
Klíčová slova:
correlation coefficient; robust statistics; image analysis
Plné texty jsou dostupné na vyžádání prostřednictvím repozitáře Akademie věd.
Robust Template Matching
In-Hospital Death Prediction in Patients with Acute Coronary Syndrome
Monhart, Z.; Reissigová, Jindra; Zvárová, Jana; Grünfeldová, H.; Janský, P.; Vojáček, J.; Widimský, P.
2013 - anglický
Klíčová slova:
acute coronary syndrome; in-hospital death; prediction; multilevel logistic regression; non-PCI hospital
Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR.
In-Hospital Death Prediction in Patients with Acute Coronary Syndrome
Objectification of a Choice of a Spa Treatment Plan for Arthritis of the Hip Joint
Och, F.; Medonos, J.; Hanzlíček, P.; Valenta, Zdeněk; Dvořák, V.; Zvárová, Jana
2013 - anglický
Klíčová slova:
decision-support; spa treatment; hip arthritis; statistical analysis
Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR.
Objectification of a Choice of a Spa Treatment Plan for Arthritis of the Hip Joint
Robustness Aspects of Knowledge Discovery
Kalina, Jan
2013 - anglický
The sensitivity of common knowledge discovery methods to the presence of outlying measurements in the observed data is discussed as their major drawback. Our work is devoted to robust methods for information extraction from data. First, we discuss neural networks for function approximation and their sensitivity to the presence of noise and outlying measurements in the data. We propose to fit neural networks in a robust way by means of a robust nonlinear regression. Secondly, we consider information extraction from categorical data, which commonly suffers from measurement errors. To improve its robustness properties, we propose a regularized version of the common test statistics, which may find applications e.g. in pattern discovery from categorical data.
Klíčová slova:
machine learning; outliers; neural networks; robust estimation
Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR.
Robustness Aspects of Knowledge Discovery
The sensitivity of common knowledge discovery methods to the presence of outlying measurements in the observed data is discussed as their major drawback. Our work is devoted to robust methods for ...
System for Selection of Relevant Information for Decision Support
Kalina, Jan; Seidl, L.; Zvára, K.; Grünfeldová, H.; Slovák, Dalibor; Zvárová, Jana
2013 - anglický
Klíčová slova:
decision support system; web-service; information extraction; high-dimension; gene expressions
Plné texty jsou dostupné na jednotlivých ústavech Akademie věd ČR.
System for Selection of Relevant Information for Decision Support
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