# Created by William La Cava (@lacava)
dataset: feynman_II_8_7
description: |
    A synthetic physics model from the Feynman Lectures on Physics.         
    This is the version of the model with units.
    Formula and simulated variable ranges given below. 
    
    E_n = 3/5*q**2/(4*pi*epsilon*d)
    
    q in [1.0,5.0]
    epsilon in [1.0,5.0]
    d in [1.0,5.0]
    
    Note the original data has been down-sampled to 100,000 rows (see source). 
source: Feynman Symbolic Regression Database https://space.mit.edu/home/tegmark/aifeynman.html 
publication: AI Feynman - a Physics-Inspired Method for Symbolic Regression, Udrescu & Tegmark (2019), arXiv:1905.11481 
task: regression
keywords: 
  - symbolic regression 
  - physics 
target: 
  type: continuous
  description: E_n, Energy, m^2 * s^(-2) * kg^1 
features: # list of features in the dataset
  - name: q
    type: continuous
    description: Charge, m^2 * s^(-2) * kg^1 * V^(-1)
  - name: epsilon
    type: continuous
    description: Electric permitivity, m^1 * s^(-2) * kg^1 * V^(-2)
  - name: d
    type: continuous
    description: Length, m^1
