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

Calculate Precision and Recall with Python

Learn calculate precision and recall with python with a short, executable Python example.

IntermediatePrecisionRecall

PROBLEM UNDERSTANDING

Input and expected output

Sample input
No input required
Sample output
0.8 0.67

COMPLETE PYTHON PROGRAM

Complete Python implementation

ai-ml-12-precision-recall.py
Open in compiler
tp, fp, fn = 8, 2, 4
print(round(tp/(tp+fp),2), round(tp/(tp+fn),2))

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

Select Start to walk through the important lines.

SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

0.8 0.67
0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

  1. Initialize the sample values used to calculate precision and recall.
  2. Apply Precision and Recall to compute the required result.
  3. Display the result for calculate precision and recall and compare it with the documented sample output.

This example of calculate precision and recall computes the result directly from the prepared sample data. It demonstrates Precision and Recall 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 precision and recall, keep the data shape and value types consistent with Precision.

Check this

Apply Precision 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.