titanic

mlr_tasks_titanic

Classification data to predict the fate of passengers on the ocean liner "Titanic".
Contains 10 features and 1309 observations. Target column is <code>"Survived"</code>.

data

A small collection of interesting and educational machine
learning data sets which are used as examples in the 'mlr3' book
(<https://mlr3book.mlr-org.com>), the use case gallery
(<https://mlr3gallery.mlr-org.com>), or in other examples. All data
sets are properly preprocessed and ready to be analyzed by most
machine learning algorithms. Data sets are automatically added to the
dictionary of tasks if 'mlr3' is loaded.

Michel Lang

mlr3data

Collection of Machine Learning Data Sets for 'mlr3'

Marc Becker

titanic function

<ul>
<li>All column names have been changed to <code>snake_case</code>.</li>
<li>training and test set have been joined.
Observations of the test set have a missing value in the target column <code>"survived"</code>.</li>
<li>Column '"survived"' has been re-encoded to a factor with levels '"yes"' and '"no"'.</li>
<li>Id column has been removed.</li>
<li>Passenger class <code>"pclass"</code> has been converted to an ordered factor.</li>
<li>Features <code>"sex"</code> and <code>"embarked"</code> have been converted to factors.</li>
<li>Empty strings in <code>"cabin"</code> and <code>"embarked"</code> have been encoded as missing values.</li>
</ul>

Pre-processing

Titanic — titanic

<ul>
<li>All column names have been changed to <code>snake_case</code>.</li>
<li>training and test set have been joined.
Observations of the test set have a missing value in the target column <code>"survived"</code>.</li>
<li>Column '"survived"' has been re-encoded to a factor with levels '"yes"' and '"no"'.</li>
<li>Id column has been removed.</li>
<li>Passenger class <code>"pclass"</code> has been converted to an ordered factor.</li>
<li>Features <code>"sex"</code> and <code>"embarked"</code> have been converted to factors.</li>
<li>Empty strings in <code>"cabin"</code> and <code>"embarked"</code> have been encoded as missing values.</li>
</ul>

titanic: Titanic

Description

Arguments

Pre-processing

Examples