Rattle provides a number of sample datasets. We can easily load them into Rattle. By default, Rattle will load the weather dataset.
We load the dataset in two simple steps
- Click on the Execute button and an example dataset is offered.
- Click on Yes to load the weather dataset.
We can use this dataset for predictive modelling to predict if it might rain tomorrow (aka statistical classification and supervised learning), or to predict how much rain we might get tomorrow (aka regression analysis).
The dataset itself is quite small, consisting of observations of some variables. Rattle also provides a much larger weather dataset covering all of Australia. The dataset has from %$ weather stattions, representing daily observations over many years.
We use the smaller dataset here for illustration, noting that typically, as data scientists, we often analyse significantly larger datasets.
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 © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0