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Effective Amazon Machine Learning by Alexis Perrier

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Validating the dataset

Not all datasets lend themselves to linear modeling. There are several conditions that the samples must verify for your linear model to make sense. Some conditions are strict, others can be relaxed.

In general, linear modeling assumes the following conditions (http://www.statisticssolutions.com/assumptions-of-multiple-linear-regression/):

  • Normalization/standardization: Linear regression can be sensitive to predictors that exhibit very different scales. This is true for all loss functions that rely on a measure of the distance between samples or on the standard deviations of samples. Predictors with higher means and standard deviations have more impact on the model and may¬†potentially overshadow predictors with better ...

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