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by Graham Williams
Duck Duck Go

MLHub Rain Tomorrow

Decision trees and the ensemble of decision trees within a random forest are two common approaches to building classification models in AI. The concept of an ensemble of decision trees was introduced in 1988 in the paper Combining Decision Trees: Initial results from the MIL algorithm where the improved performance from multiple trees is demonstrated. The rattle package in R provides the weatherAUS dataset which is used to predict rain tomorrow. This is the dataset used to build the model that is demonstrated in these MLHub packages: rain and rainrf.

These MLHub packages also demonstrate how to deliver multiple MLHub models from a single git repository. This one repository contains a yaml file for the rain model (MLHUB.yaml) and another yaml file for the rainrf model (rainrf.yaml).

Here we install, configure and demonstrate the rain model, a decision tree model for predicting whether it will rain tomorrow:

$ ml install rain
$ ml configure rain
$ ml demo rain

Support further development by purchasing the PDF version of the book.
Other online resources include the Data Science Desktop Survival Guide.
Books available on Amazon include Data Mining with Rattle and Essentials of Data Science.
Popular open source software includes rattle and wajig.
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