Actual
How to Interpret Machine Learning Model Results
Evaluating AI Models
How to Validate Models
How to Interpret Machine Learning Results
Analyzing Machine Learning Results
Metrics
Performance
Machine Learning Model Evaluation 
Recall (Sensitivity) The ratio of true positive predictions to the total
actual positives
...
How to Interpret Machine Learning Model Results Mean Absolute Error (MAE) The average absolute difference between predicted and
actual values
...
Evaluating AI Models Recall (Sensitivity) Classification Proportion of true positives among all
actual positives
...
How to Validate Models Recall (Sensitivity): The ratio of true positive predictions to the total
actual positives
...
How to Interpret Machine Learning Results Classification Recall (Sensitivity) The ratio of true positive predictions to the
actual positives
...
Analyzing Machine Learning Results Recall (Sensitivity) Classification Measures the proportion of true positive predictions out of all
actual positive instances
...
Metrics Diagnostic Metrics: These metrics help identify the causes of performance issues by comparing
actual performance against benchmarks
...
Performance Recall (Sensitivity) Proportion of true positive predictions to the
actual positives
...
Sales Metrics Actual Sales / Sales Target) x 100 Customer Acquisition Cost (CAC) The total cost of acquiring a new customer, including marketing and sales expenses
...
Evaluating Predictive Success Recall (Sensitivity) Proportion of true positive results in all
actual positive cases
...
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