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Performance evaluation and visualization with one function call

Project description

Complete Confusion

A simple call to visualize performance metrics for classification and regression models.

Installation

pip install complete-confusion

Usage

import complete_confusion as cc

# Example data
predictions = [0, 1, 0, 2, 1, 2, 0]
trues = [0, 1, 0, 2, 0, 2, 2]
classes = ["Class 0", "Class 1", "Class 2"]
output_path = "confusion_matrix.html"

cc.export_confusion_matrix_to_html(predictions, trues, classes, output_path)

Development

poetry install
poetry shell
python evaluate.py

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