## Friedman-1 synthetic dataset

Generate a synthetic dataset using the Friedman-1 function implemented in StatSim

In [1]:
from iframer import *
iframer('https://statsim.com/app/?m=friedman1&preview=1')


## Friedman-1 model¶

This dataset was described in the Multivariate Adaptive Regression Splines paper by Jerome H. Friedman in 1991. All features $\mathbf{x}$ are independent uniform random variables taking values from 0 to 1. The output $y$ is calculated with the formula:

$$f(\mathbf{x}) = 10 sin(\pi x_1 x_2) + 20 (x_3 - 0.5)^2 + 10 x_4 + 5 x_5 + \mathcal{N}(0, sigma)$$

By default ten $\mathbf{x}$ variables are generated, from which only first 5 are used in the formula. That makes this dataset useful for testing feature selection methods too.