forecasting:meeting_minutes_september_16_2020

Attended: Josh, Keola

  • Started Section 8 of the course: Polynomial Regression
  • Topics learned: Polynomial Regression Intuition, implementation in python
  • COVID-19 forced today's lab hours to be online
  • PolynomialFeatures(degree = ).fit_transform is used to create a matrix where each value of your independent variable, x, is organized into row arrays based on the degree
  • If you have features [a, b, c] the default polynomial features(in sklearn the degree is 2) should be [1, a, b, c, a^2, b^2, c^2, ab, bc, ca].
  • If you have features [1] and degree = 2, the matrix should give [1, 1, 1,]
  • If you have features [2] and degree = 2, the matrix should give [1, 2, 4,]
  • If you have features [3] and degree = 2, the matrix should give [1, 3, 9,]

Authors

Contributing authors:

jclaudio

Created by jclaudio on 2020/09/19 22:07.

  • forecasting/meeting_minutes_september_16_2020.txt
  • Last modified: 2021/09/19 21:59
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