Sampling of Variable (Small Samples) in Machine Learning
In practical problems, we cannot always have a large sample on account of economical factors, therefore we have to depend on a small sample (<30). Since the samples are small we cannot assume as in the case of large sample that the random sampling distribution of a parameter is approximately normal. Secondly, the estimates of parameters of the population made from a small sample are not reliable.
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Algorithm For Loss Function and introduction
Common Loss functions in machine learning- 1)Regression losses and 2)Classification losses . There are three types of Regression losses...
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Common Loss functions in machine learning- 1)Regression losses and 2)Classification losses . There are three types of Regression losses...
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-- | -- Module : Algorithms.MDP -- Copyright : Patrick Steele 2015 -- License : MIT (see the LICENSE file) -- Maintainer : prs23...
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