A Walk-through-guide for Using Decision Trees Software - Data Mining with Decision Trees: Theory and Applications - page 152

Table 10.1 The Iris dataset consists of four numeric features and three possible
classes.
Sepal Length Sepal Width Petal Length Petal Width Class (Iris Type)

5.1 3.5 1.4 0.2 Iris-setosa

4.9 3.0 1.4 0.2 Iris-setosa

6.0 2.7 5.1 1.6 Iris-versicolor

5.8 2.7 5.1 1.9 Iris-virginica

5.0 3.3 1.4 0.2 Iris-setosa

5.7 2.8 4.5 1.3 Iris-versicolor

5.1 3.8 1.6 0.2 Iris-setosa

.

10.2 Weka

Weka is a popular machine learning suit developed at the University of
Waikato. Weka is an open source software written in Java and available
under the GNU General Public License.
The latest version and installation instructions can be down-
loaded from: http://www.cs.waikato.ac.nz/ ∼ ml/weka/downloading.
html . Note that from version 3.7.2, Weka is installed with only the most
popular learning algorithms. In order to install other algorithms one should
use the package manager to select which additional component is to be
installed. The Inventors of Weka have written a topic that provides a
detailed description of the Weka suite [Witten et al . (2011)].Thebook
is very popular and it is highly cited (more than 20,000 citations until 2013
according to Google Scholar). In this section, we only provide a brief step-
by-step description on how to use Weka for training classification trees.
We begin by initiating the main Weka application. A window with
Weka GUI Chooser is opened. For our walk-through-guide we choose the
Explorer application. After clicking the Explorer button, the explorer
window is opened. At the top of the new window, one can find a tab
that corresponds to various tasks (see Figure 10.1) such as: preprocess,
classification, clustering etc. At this stage, since no data has been loaded
yet, the only task that is available is the preprocess task.
In the preprocess tab, please click the open file and using the windows
explorer load the Iris dataset. The Iris dataset is distributed as part of the
Weka installation in the $WEKAHOME/data directory, where $WEKAHOME is
the directory of your Weka installation (in Windows the default location
is C:/ProgramFiles/Weka-3-X , where x stands for the installed version).