The easiest way to think of a spline is to first think of linear regression – a single linear relationship between an outcome variable and various predictor variables.
The easiest way to think of a spline is to first think of linear regression – a single linear relationship between an outcome variable and various predictor variables.
To some, NLP = natural language processing, a form of text analytics arising from the field of computational linguistics.
As applied to statistical models – “overfit” means the model is too accurate, and fitting noise, not signal. For example, the complex polynomial curve in the figure fits the data with no error, but you would not want to rely on it to predict accurately for new data: