Data
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mkl-splice - submitted by mkloft 2441 views, 8480 downloads, 0 comments
last edited by mkloft - May 28, 2015, 16:20 CET Rating
- Summary:
Splice Site Detection Using Multiple Kernels (20 WD Kernels)
- Data Shape: 20 attributes, 1000 instances ()
- License: unknown
- Tags: MKL
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (503.6 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Splice Site Detection Using Multiple Kernels (20 WD Kernels)
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MKL-toy - submitted by mkloft 570 views, 17161 downloads, 0 comments
last edited by mkloft - Sep 14, 2011, 15:43 CET Rating
- Summary:
Multiple kernel toy data set (six different scenarios)
- Data Shape: 40304 attributes, 20050 instances ()
- License: CC0
- Tags: Kernel Learning MKL Multiple
- Tasks / Methods / Challenges: 1 tasks, 0 methods, 0 challenges
- Download: HDF5 (46.1 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Multiple kernel toy data set (six different scenarios)
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TSS - submitted by mkloft 0 views, 8754 downloads, 0 comments
last edited by mkloft - May 31, 2013, 00:52 CET Rating
- Summary:
Transcription Start Site Detection with Multiple Kernels
- Data Shape: 3 attributes, 2000 instances ()
- License: unknown
- Tags: ARTS detection Kernel Kernels Learning MKL Multiple Site start Transcription TSS
- Tasks / Methods / Challenges: 0 tasks, 0 methods, 0 challenges
- Download: HDF5 (152.6 MB) XML CSV ARFF LibSVM Matlab Octave
- Files are converted on demand and the process can take up to a minute. Please wait until download begins.
- Summary:
Transcription Start Site Detection with Multiple Kernels
Disclaimer
We are acting in good faith to make datasets submitted for the use of the scientific community available to everybody, but if you are a copyright holder and would like us to remove a dataset please inform us and we will do it as soon as possible.
Acknowledgements
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
http://www.pascal-network.org/.