Trending Technology Machine Learning, Artificial Intelligent, Block Chain, IoT, DevOps, Data Science

Recent Post

Codecademy Code Foundations

Search This Blog

Ordinary Least Squares Regression in Data Analytics

Ordinary Least Squares (OLS)
  • Context:
           → Supervised Learning
  • Derivation of OLS
           → Fit a line of the form y = mx + c  or y = b0 + b1x
          
 → Concept of actual y (𝐲i) and estimated y (ỷi)
          
  → Minimize the squared deviation between actual and estimate.

The Derivation :-


Derivation :-
  • Our goal is to minimize SSE: 
                SSE = ∑ (yi - b0 - b1xi)2
  • We use basic ideas from calculus: Take the first derivative and equate it to 0.

Derivation for b0


Derivation of b1

 

No comments:

Post a Comment

Popular Posts