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The performance of unsupervised biology-inspired clustering algorithms applied to artificial datasets with different size of dimension
Main topics of the document: k-means; neural Gas; SOM; high; dimensional space; biology-inspired clustering; artificial datasets; size of dimensions......
BB - Aplikovaná statistika, operační výzkum
- 2012 •
- D
Rok uplatnění
D - Stať ve sborníku
Combined method for effective clustering based on parallel SOM and spectral clustering
The paper is oriented to the problem of clustering for large datasets with high-dimensions. We propose a two-phase combined method with regard to high dimensions operation (especially for large highdimensi...
IN - Informatika
- 2011 •
- D
Rok uplatnění
D - Stať ve sborníku
Effective Clustering Algorithm for High-Dimensional Sparse Data Based on SOM
With increasing opportunities for analyzing large data sources, we have noticed a lack of effective processing in datamining tasks working with large sparse datasets of high dimensions. This work focuses on this issue and o...
IN - Informatika
- 2013 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Minimum Redundancy Maximum Relevance variable selection 1.0
The code implemented in R software performs supervised variable selection of a given (possibly high-dimensional) dataset by the MRMR method, i.e. Minimum Redundancy-Maximum Relevance. The computations, which were tested ove...
Statistics and probability
- 2020 •
- R •
- Link
Rok uplatnění
R - Software
Výsledek na webu
Parallel Hybrid SOM Learning on High Dimensional Sparse Data
of projecting high-dimensional space into lower dimensions. There are commonly discussed representation in the high-dimensional space. In the paper there is proposed the effective clustering algorithm bas...
IN - Informatika
- 2011 •
- D
Rok uplatnění
D - Stať ve sborníku
Fast Dimension Reduction Based on NMF
Non-negative matrix factorization is an important method in the analysis of high dimensional datasets. It has a number of applications including pattern recognition, data clustering, information retrieval or computer securi...
IN - Informatika
- 2010 •
- D
Rok uplatnění
D - Stať ve sborníku
Finding the optimal number of low dimension with locally linear embedding algorithm
number of dimension when using dimensionality reduction methods, and in this paper in the original data and in the low-dimensional data. Finally, the optimal low dimension data and in the data after dimensiona...
Communication engineering and systems
- 2021 •
- Jimp •
- Link
Rok uplatnění
Jimp - Článek v periodiku v databázi Web of Science
Výsledek na webu
A comparative study of two methodologies for binary datasets analysis
Main topics of the document: dimension reduction; Boolean matrix factorization; likelihood-maximization...
BB - Aplikovaná statistika, operační výzkum
- 2012 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Aggregate Function Generalization to Temporal Data
of the parameters. We then apply a common regularized linear model to train a model on this high-dimensional space. Experimental results on 11 datasets suggest that there are datasets where incorporating time ...
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
- 2021 •
- D •
- Link
Rok uplatnění
D - Stať ve sborníku
Výsledek na webu
Search for dark matter candidates and large extra dimensions in events with a jet and missing transverse momentum with the ATLAS detector
A search for new phenomena in events with a high-energy jet and large missing transverse momentum is performed using data from proton-proton collisions at root s = 7 regions areexplored using a dataset corresponding to an integrated...
BF - Elementární částice a fyzika vysokých energií
- 2013 •
- Jx •
- Link
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Výsledek na webu
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