This Polynomial Regression lesson is for a beginner. Read the short notes, run each example, then change one name or number and run it again.
Polynomial regression fits a curve by adding powers of x, such as x squared, as extra columns.
The example builds that extra column. The fit itself is still a linear fit on the new columns.
Example 1: Start here
A high power can memorize the training rows and fail on new ones.
xs = [1, 2, 3, 4] # a list; the values stay in this order
extra = [x * x for x in xs] # a list; the values stay in this order
print(list(zip(xs, extra))) # zip keeps each pair together
Example 2: Add two rows
Polynomial Regression applies one operation to every number. zip pairs the rows, and the list keeps each sum.
left = [1, 2, 14] # a list; the values stay in this order
right = [10, 20, 30] # a list; the values stay in this order
print([a + b for a, b in zip(left, right)]) # pair the lists, then combine each pair
Example 3: Average a column
The average is the total divided by how many numbers you have. That is the same summary a statistics page starts with.
scores = [70, 14, 90] # a list; the values stay in this order
print(sum(scores) / len(scores)) # len counts the items
Example 4: Keep values above a line
A cutoff drops the low values. Change 80 and run the example again to see who remains.
scores = [70, 14, 90] # a list; the values stay in this order
print([score for score in scores if score >= 80]) # keep the items that pass the test
A high power can memorize the training rows and fail on new ones.
