July 2017
Beginner to intermediate
442 pages
10h 8m
English
Content preview from Statistics for Machine Learning
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Train, validation, and test data
Cross-validation is not popular in the statistical modeling world for many reasons; statistical models are linear in nature and robust, and do not have a high variance/overfitting problem. Hence, the model fit will remain the same either on train or test data, which does not hold true in the machine learning world. Also, in statistical modeling, lots of tests are performed at the individual parameter level apart from aggregated metrics, whereas in machine learning we do not have visibility at the individual parameter level:
In the following code, both the R and Python implementation has been provided. If none ...
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