How To Get Baseline Results And Why They Matter
Last Updated on June 27, 2017
In my courses and guides, I teach the preparation of a baseline result before diving into spot checking algorithms.
A student of mine recently asked:
If a baseline is not calculated for a problem, will it make the results of other algorithms questionable?
He went on to ask:
If other algorithms do not give better accuracy than the baseline, what lesson should we take from it? Does it indicate that the data set does not have prediction capability?
These are great questions, they get to the heart of why we create a baseline in the first place and the filtering power it provides.
In this post, you will learn why we create a baseline prediction result, how to create a baseline in general and for specific problem types, and how you can use it to inform you on the data you have available and the algorithms you are using.
Baseline Machine Learning Results
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