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|Created||Wed, 27 Jul 2016 06:56:53 +0000|
|Published||Wed, 27 Jul 2016 07:31:28 +0000|
A very simple script in which we decide whether it's better to use a model or an ensemble for making predictions by creating both (given an input source) and evaluating the results, choosing the one with best
f-1 measure in its evaluation if the objective field is categorical, or
r-measure for regression problems.
Given an input dataset:
Create a dataset with the input source.
Split it into training and test parts (80%/20%).
Create a model using the training dataset.
Create an ensemble using the training dataset.
Evaluate both the model and the ensemble using the test dataset.
Compare their evaluations and choose the best.