Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Daniel Ahfock"'
Autor:
Daniel Ahfock, Geoffrey J. McLachlan
Publikováno v:
Econometrics and Statistics. 26:124-138
There has been increasing attention to semi-supervised learning (SSL) approaches in machine learning to forming a classifier in situations where the training data for a classifier consists of a limited number of classified observations but a much lar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1351e11ad126d8f0e3efc137e5d4b22a
https://doi.org/10.1016/j.ecosta.2022.03.007
https://doi.org/10.1016/j.ecosta.2022.03.007
Publikováno v:
Statistics and Computing. 33
There is an increasing body of work exploring the integration of random projection into algorithms for numerical linear algebra. The primary motivation is to reduce the overall computational cost of processing large datasets. A suitably chosen random
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::437ae9b34aee06a3fcc986339d209bd8
https://doi.org/10.1007/s11222-022-10148-5
https://doi.org/10.1007/s11222-022-10148-5
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b93634110f83ff6bf5c8bf9d57a717b1
https://doi.org/10.2139/ssrn.4097818
https://doi.org/10.2139/ssrn.4097818
Publikováno v:
Statistics and Computing. 31
Data fusion involves the integration of multiple related datasets. The statistical file-matching problem is a canonical data fusion problem in multivariate analysis, where the objective is to characterise the joint distribution of a set of variables
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::313b5dcde831ee28e151d31bd7da36a6
https://doi.org/10.1007/s11222-021-10033-7
https://doi.org/10.1007/s11222-021-10033-7
Publikováno v:
Australian & New Zealand Journal of Statistics. 61:175-188
We present an application study which exemplifies a cutting edge statistical approach for detecting climate regime shifts. The algorithm uses Bayesian computational techniques that make time-efficient analysis of large volumes of climate data possibl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::034d5dd859b390b17d8e3a7c977dded8
https://doi.org/10.1111/anzs.12265
https://doi.org/10.1111/anzs.12265
Autor:
Daniel Ahfock, Geoffrey J. McLachlan
Publikováno v:
Data Analysis and Rationality in a Complex World ISBN: 9783030601034
We consider the situation where the observed sample contains some observations whose class of origin is known (that is, they are classified with respect to the g underlying classes of interest), and where the remaining observations in the sample are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::804660f7e9210024fea102f10e8c5399
https://doi.org/10.1007/978-3-030-60104-1_17
https://doi.org/10.1007/978-3-030-60104-1_17
Publikováno v:
Computational Statistics & Data Analysis. 168:107387
The statistical file-matching problem is a data integration problem with structured missing data. The general form involves the analysis of multiple datasets that only have a strict subset of variables jointly observed across all datasets. Missing-da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::641a145a0b089f4ac7b5b0b10a038c9f
https://doi.org/10.1016/j.csda.2021.107387
https://doi.org/10.1016/j.csda.2021.107387
Autor:
Daniel Ahfock, Geoffrey J. McLachlan
Publikováno v:
Computational Statistics & Data Analysis. 161:107253
Manual labelling of training examples is common practice in supervised learning. When the labelling task is of non-trivial difficulty, the supplied labels may not be equal to the ground-truth labels, and label noise is introduced into the training da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::819032145893f9c9f713ff5302094a9a
https://doi.org/10.1016/j.csda.2021.107253
https://doi.org/10.1016/j.csda.2021.107253
Publikováno v:
Computational statistics & data analysis
The statistical matching problem involves the integration of multiple datasets where some variables are not observed jointly. This missing data pattern leaves most statistical models unidentifiable. Statistical inference is still possible when operat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a52f745acb4ed50594063f306a4a86b9
http://europepmc.org/articles/PMC5423529
http://europepmc.org/articles/PMC5423529
Publikováno v:
Biometrika
Sketching is a probabilistic data compression technique that has been largely developed in the computer science community. Numerical operations on big datasets can be intolerably slow; sketching algorithms address this issue by generating a smaller s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af061ee9bf98210cfa6aed3081704851
http://arxiv.org/abs/1706.03665
http://arxiv.org/abs/1706.03665