AI & MACHINE LEARNING PROGRAM • LEVEL 07 — LOGISTIC CLASSIFICATION

Make a Binary Prediction with Python

Learn make a binary prediction with python with a short, executable Python example.

IntermediateLogistic regressionThreshold

PROBLEM UNDERSTANDING

Input and expected output

Sample input

No input required

Sample output

0.769 1

COMPLETE PYTHON PROGRAM

Complete Python implementation

from math import exp
score = -0.4 + 0.8 * 2
probability = 1 / (1 + exp(-score))
print(round(probability, 3), int(probability >= 0.5))

CURRENT STEP

Select Start to walk through the important lines.

SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

0.769 1

0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

Import the required standard-library tools and prepare the sample data for make a binary prediction.
Apply Logistic regression and Threshold to compute the required result.
Display the result for make a binary prediction and compare it with the documented sample output.

This example of make a binary prediction computes the result directly from the prepared sample data. It demonstrates Logistic regression and Threshold 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 make a binary prediction, keep the data shape and value types consistent with Logistic regression.

Check this

Apply Logistic regression 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.