November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Learning curves
Another method of assessing a statistical model's performance is by evaluating the model's growth of learning or the model's ability to improve learning (obtain a better score) with additional experience (for example, more rounds of cross-validation).
The phrase, with additional experience, is vitally important in statistics as we not only look for a statistical model to perform well on a given population of data, but we hope that the model's performance will improve as it is trained and tested on more and more data.
The information indicating a model's performance, result, or score with a data file population is usually combined with other scores to show a line or curve—this is known as the statistical model's learning curve. ...
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