Source: ask Maintainer: Debian Science Maintainers Uploaders: Pablo Oliveira Section: science Priority: optional Build-Depends: debhelper (>= 12~), texlive-latex-base, texlive-latex-extra, texlive-latex-recommended, python, python-pygments, python-nose, python-argparse, python-numpy, python-scipy, python3-pygments, python3-pkg-resources, r-base-core, r-cran-gbm, r-cran-rpart, r-cran-lattice, r-cran-rjson, r-cran-lhs, r-cran-tgp (>=2.4-14-2), r-cran-inline, r-cran-foptions Standards-Version: 4.3.0 Vcs-Browser: https://salsa.debian.org/science-team/ask Vcs-Git: https://salsa.debian.org/science-team/ask.git Homepage: https://github.com/benchmark-subsetting/adaptive-sampling-kit Package: ask Architecture: all Depends: ${python:Depends}, ${misc:Depends}, python, python-argparse, python-numpy, python-scipy, r-base-core, r-cran-gbm, r-cran-rpart, r-cran-lattice, r-cran-rjson, r-cran-lhs, r-cran-tgp (>=2.4-14-2), r-cran-inline, r-cran-foptions Description: Adaptive Sampling Kit for big experimental spaces Adaptive Sampling Kit (ASK) is a toolkit for sampling big experimental spaces. When the space is small, the response can be measured for every point in the space. When the space is large, doing an exhaustive measurement is either not possible in terms of execution time or simply not practical. ASK tries to find good approximations of the response by sampling only a small fraction of the space. ASK features multiple active learning algorithms to prioritize the exploration of the interesting parts of the experimental space.