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AI & MACHINE LEARNING PROGRAM • LEVEL 12 — EVALUATION & TUNING

Calculate F1-score with Python

Learn calculate f1-score with python with a short, executable Python example.

IntermediateF1-scoreImbalanced data

PROBLEM UNDERSTANDING

Input and expected output

Sample input
No input required
Sample output
0.615

COMPLETE PYTHON PROGRAM

Complete Python implementation

ai-ml-12-f1-score.py
Open in compiler
precision, recall = 0.8, 0.5
f1 = 2*precision*recall/(precision+recall)
print(round(f1,3))

GUIDED CODE TOUR • NOT LIVE EXECUTION

Study the program line by line

Use the real compiler button above to run and debug with different inputs.

CURRENT STEP

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SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

0.615
0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

  1. Initialize the sample values used to calculate f1-score.
  2. Apply F1-score and Imbalanced data to compute the required result.
  3. Display the result for calculate f1-score and compare it with the documented sample output.

This example of calculate f1-score computes the result directly from the prepared sample data. It demonstrates F1-score and Imbalanced data and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(1)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

Check this

For calculate f1-score, keep the data shape and value types consistent with F1-score.

Check this

Apply F1-score in the same order shown by the algorithm; changing the order can change the result.

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.