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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Assessment
When a data scientist evaluates a model or data science process for performance, this is referred to as assessment. Performance can be defined in several ways, including the model's growth of learning or the model's ability to improve (with) learning (to obtain a better score) with additional experience (for example, more rounds of training with additional samples of data) or accuracy of its results.
One popular method of assessing a model or processes performance is called bootstrap sampling. This method examines performance on certain subsets of data, repeatedly generating results that can be used to calculate an estimate of accuracy (performance).
The bootstrap sampling method takes a random sample of data, splits it into three ...
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