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If the above conditions are not satisfied, it is possible that there are some missing/hidden factors/predictor variables that have not been taken into account. Residual plot is available for numerical prediction models. You can select a dataset feature to be plotted with its residuals.
Precision and Recall
Precision and Recall are performance measures used to evaluate search strategies. They are typically used in document retrieval scenarios.
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| Measure | Definition | Formula | ||
|---|---|---|---|---|
| Precision | The number of the records relevant to the search that are retrieved, as a percentage of the total number of records in the database. | TP / (TP + FP) | ||
| Recall | The number of the records relevant to the search that are retrieved, as a percentage of the total number of records that are relevant to the search.
| TP / (TP + FN) |
F1 Score
The F1 Score gives the weighted average of Precision and Recall. It is expressed as a value between 0 and 1, where 0 indicates the worst performance and 1 indicates the best performance.
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