#44 Machine Learning & Data Science Challenge 44
Greetings.
I am a machine learning engineer based in India, possessing a sustained interest in machine learning since my undergraduate studies. I have completed Stanford University's machine learning course (Andrew Ng) via Coursera, and IBM's machine learning and deep learning curriculum. My current focus is on machine learning and data science projects, aiming to leverage my expertise for impactful, real-world problem-solving.
What is Mean Absolute Error?
What is Absolute Error?
Absolute Error is the amount of error in your measurements.
It is the difference between the measured value and the “true” value.
For example, if a scale states 90 pounds, but you know your true weight is 89 pounds, then the scale has an absolute error of 90 lbs – 89 lbs = 1 lbs.
Mean Absolute Error
The Mean Absolute Error(MAE) is the average of all absolute errors.
Formula:
Where,
n = the number of errors
Σ = summation symbol (which means “add them all up”)
|xi – x| = the absolute errors
- The formula may look a little daunting, but the steps are easy:
Find all of your absolute errors
xi – x. Add them all up
Divide by the number of errors
