mlr_tasks_spam

Spam data set from the UCI machine learning repository (<a href="http://archive.ics.uci.edu/ml/datasets/spambase">http://archive.ics.uci.edu/ml/datasets/spambase</a>).
Data set collected at Hewlett-Packard Labs to classify emails as spam or non-spam.
57 variables indicate the frequency of certain words and characters in the e-mail.
The positive class is set to "spam".

Efficient, object-oriented programming on the
building blocks of machine learning. Provides 'R6' objects for tasks,
learners, resamplings, and measures. The package is geared towards
scalability and larger datasets by supporting parallelization and
out-of-memory data-backends like databases. While 'mlr3' focuses on
the core computational operations, add-on packages provide additional
functionality.

Michel Lang

mlr3

Machine Learning in R - Next Generation

Bernd Bischl

Jakob Richter

Patrick Schratz

Giuseppe Casalicchio

Stefan Coors

Quay Au

Martin Binder

mlr_tasks_spam function

<a rd-options="R6:R6Class" href="/link/R6%3A%3AR6Class?package=mlr3&version=0.2.0&to=R6%3AR6Class" data-mini-rdoc="R6:R6Class::R6::R6Class">R6::R6Class</a> inheriting from <a rd-options="" href="/link/TaskClassif?package=mlr3&version=0.2.0" data-mini-rdoc="mlr3::TaskClassif">TaskClassif</a>.

Format

<pre>mlr_tasks$get("spam")
tsk("spam")
</pre>

Construction

Spam data set from the UCI machine learning repository (<a href='http://archive.ics.uci.edu/ml/datasets/spambase'>http://archive.ics.uci.edu/ml/datasets/spambase</a>).
Data set collected at Hewlett-Packard Labs to classify emails as spam or non-spam.
57 variables indicate the frequency of certain words and characters in the e-mail.
The positive class is set to "spam".

Spam Classification Task — mlr_tasks_spam

<a rd-options='R6:R6Class' href='R6::R6Class'>R6::R6Class</a> inheriting from <a rd-options='' href='TaskClassif'>TaskClassif</a>.

mlr_tasks_spam: Spam Classification Task

Description

Arguments

Format

Construction

References

See Also