AI & MACHINE LEARNING PROGRAM • LEVEL 06 — LINEAR REGRESSION

Calculate R-squared with Python

Learn calculate r-squared with python with a short, executable Python example.

IntermediateR-squaredRegression metric

PROBLEM UNDERSTANDING

Input and expected output

Sample input

No input required

Sample output

0.75

COMPLETE PYTHON PROGRAM

Complete Python implementation

actual = [2, 4, 6]
predicted = [2, 5, 5]
mean = sum(actual)/len(actual)
r2 = 1 - sum((a-p)**2 for a,p in zip(actual,predicted)) / sum((a-mean)**2 for a in actual)
print(round(r2, 3))

CURRENT STEP

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SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

0.75

0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

Initialize the sample values used to calculate r-squared.
Process the data step by step using R-squared and Regression metric.
Display the result for calculate r-squared and compare it with the documented sample output.

This example of calculate r-squared processes the sample values in a controlled iteration. It demonstrates R-squared and Regression metric and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(n)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

Check this

For calculate r-squared, keep the data shape and value types consistent with R-squared.

Check this

Keep every dependent statement inside the correct indented Python block.

Check this

Check denominators, numeric ranges and rounding before comparing the calculated value.

Try it yourself

Practice: Run the program with the sample input, predict its output, and then test one boundary case of your own.