Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Kari Torkkola"'
Publikováno v:
International Journal of Forecasting. 38:1473-1481
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e9ff990be689118d361f25c8bf82d44
https://doi.org/10.1016/j.ijforecast.2021.10.004
https://doi.org/10.1016/j.ijforecast.2021.10.004
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 50:2438-2442
Manually annotating large databases in any domain is costly and time-consuming. We present a semi-automatic annotation tool for this purpose that uses Random Forests as bootstrapped classifiers. We describe an application of this tool on a large data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b08ebf551c1c5c20ad7e041a48256e36
https://doi.org/10.1177/154193120605002219
https://doi.org/10.1177/154193120605002219
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 28:1385-1392
A classification system typically consists of both a feature extractor (preprocessor) and a classifier. These two components can be trained either independently or simultaneously. The former option has an implementation advantage since the extractor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b711e84e203d7453efc2809f156c5d6b
https://doi.org/10.1109/tpami.2006.186
https://doi.org/10.1109/tpami.2006.186
Autor:
Michael E. Berens, Hanchuan Peng, Chris Ding, Lei Yu, Fuhui Long, Zheng Zhao, Eugene Tuv, Lance Parsons, Jennifer G. Dy, George Forman, Edward R. Dougherty, Kari Torkkola, Huan Liu
Publikováno v:
IEEE Intelligent Systems. 20:64-76
Data preprocessing is an indispensable step in effective data analysis. It prepares data for data mining and machine learning, which aim to turn data into business intelligence or knowledge. Feature selection is a preprocessing technique commonly use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8dcfb13ec04295ad80452fa8cfdbd3d
https://doi.org/10.1109/mis.2005.105
https://doi.org/10.1109/mis.2005.105
Publikováno v:
Information Sciences. 139:79-96
Modern DNA microarray technology provides means of measuring gene expression patterns of the whole genome of simple organisms at once. Exploratory analysis of these large-scale expression datasets is becoming vital to extracting functional informatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3c3a4ccec814bb37d5233e0ec1a0286
https://doi.org/10.1016/s0020-0255(01)00158-x
https://doi.org/10.1016/s0020-0255(01)00158-x
Publikováno v:
Speech Communication. 14:119-130
In the framework of phonemic speech recognition using Hidden Markov Models (HMMs) together with codebooks trained by Learning Vector Quantization (LVQ), a novel way to model context-dependencies in speech is presented. We use LVQ to map acoustic cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ece79f7cfc4969b0d09d2bfcd87d4c4
https://doi.org/10.1016/0167-6393(94)90003-5
https://doi.org/10.1016/0167-6393(94)90003-5
Publikováno v:
Folia Phoniatrica et Logopaedica. 45:135-144
The [s] samples of 11 women, psychoacoustically classified as acceptable/unacceptable, were studied with the self-organizing map, the neural network algorithm of Kohonen. The measurement map had been previously computed with nondisordered speech samp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::814ac3f5a36fbf43a4b798af5c17c6c9
https://doi.org/10.1159/000266239
https://doi.org/10.1159/000266239
Autor:
Kari Torkkola, Michael R. Gardner, John Summers, Keshu Zhang, Harry Zhang, Bob Leivian, C. Schreiner
Publikováno v:
Studies in Computational Intelligence ISBN: 9783540792567
Computational Intelligence in Automotive Applications
Computational Intelligence in Automotive Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c1c3284e36c5c2c0c906ed3e789653e
https://doi.org/10.1007/978-3-540-79257-4_3
https://doi.org/10.1007/978-3-540-79257-4_3
Autor:
Kari Torkkola, Eugene Tuv
Publikováno v:
Data Mining: Foundations and Practice ISBN: 9783540784876
Data Mining: Foundations and Practice
Data Mining: Foundations and Practice
For the recent NIPS-2003 feature selection challenge we studied ensembles of regularized least squares classifiers (RLSC). We showed that stochastic ensembles of simple least squares kernel classifiers give the same level of accuracy as the best sing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec27035c29a4504f1754724a375d378c
https://doi.org/10.1007/978-3-540-78488-3_22
https://doi.org/10.1007/978-3-540-78488-3_22
Publikováno v:
Computational Methods of Feature Selection ISBN: 9781584888789
Computational Methods of Feature Selection
Computational Methods of Feature Selection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ece779704dc316d4b5abdd51c645cbf4
https://doi.org/10.1201/9781584888796.ch7
https://doi.org/10.1201/9781584888796.ch7