For R based models it is often useful to
install some R packages through the operating system, especially those
that are identified as
system dependencies in
dependencies are installed locally for the user if they have not
already been installed on the system. For this case some useful
packages to pre-install are identified below. This can be done at any
time, but is useful before installing any of the R based MLHub
packages. Users will not then individually need to install the
packages for themselves.
$ R > install.packages(c("rpart", "tidyverse"))
Similarly for common Python dependencies. One particular example is tensorflow which does not have a Ubuntu package and thus is installed using pip. This can be installed any time, and any mlhub package that requires tensorflow will not need to install it separately.
$ pip install tensorflow
If you have system administrator access (generally through the
sudo command) then you may want to checkout a
MLHUB.yaml file to install any dependencies on the system,
rather than per user when they install the MLHub package.
If a model has installed badly, got corrupted, or not working as expected, sometimes an uninstall followed by install will fix the problem. When uninstalling in these circumstances it is usually a good idea to remove the cache as well:
$ ml uninstall objects Remove '/home/kayon/.mlhub/objects/' [Y/n]? y Remove cache '/home/kayon/.mlhub/.cache/objects/' as well [y/N]? y $ ml install objects
Commands Auto Completion
The bash shell on Linux supports command line auto-completion which is
pretty handy. You can download ml.bash
from the MLHub and place the file into
~/.local/share/bash-completion/completions/ for recent versions of
bash, or into the system-wide location
configure command installs the file into the
system-wide location. Be sure to restart the shell for the
auto-completion to take effect.
Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0