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Home
Python 3
Introduction to Model Evaluation

Introduction to Model Evaluation

Introduction to Model Evaluation

Introduction to Model Evaluation

Building a machine learning model is only the first step. To understand how well the model performs, we need to evaluate it using different performance metrics.

Model evaluation helps answer questions such as:

How many reviews were classified correctly?
How many fake reviews were missed?
How many genuine reviews were incorrectly labeled as fake?
Can the model be trusted in real-world applications?

Instead of relying only on accuracy, we use multiple evaluation metrics to obtain a more comprehensive understanding of the model's performance.

The evaluation metrics covered in this module are:

Confusion Matrix
Classification Report
Precision
Recall
F1-Score
ROC Curve
AUC Score

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Introduction to Model Evaluation

Contents

Introduction to Model Evaluation

Fake Review Detection System using Machine Learning

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