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Effective Amazon Machine Learning by Alexis Perrier

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Assumptions for multiclass linear models

For a linear model to offer reliable predictions, predictors must satisfy a certain number of conditions. These conditions are known as the Assumptions of Multiple Linear Regression (http://www.statisticssolutions.com/assumptions-of-multiple-linear-regression/):

  • Linear relationship: The predictors should have some level of linear relationship with the outcome
  • Multivariate normality: The predictors should follow a Gaussian distribution
  • No or little multicollinearity: The predictors should not be correlated to one another
  • Homoscedasticity: The variance of each predictor should remain more or less constant across the whole range of values

Of course, these assumptions are seldom verified. But there are ...

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