Achilleas Pasias commited on
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Update Readme

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  1. README.md +2 -8
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@@ -7,19 +7,13 @@ sdk: gradio
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  sdk_version: 3.17.0
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  app_file: app.py
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  pinned: false
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- ---
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  tags:
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  - evaluate
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  - metric
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  description: >-
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- Accuracy is the proportion of correct predictions among the total number of cases processed. It can be computed with:
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- Accuracy = (TP + TN) / (TP + TN + FP + FN)
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- Where:
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- TP: True positive
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- TN: True negative
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- FP: False positive
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- FN: False negative
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  ---
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  # Metric Card for Confusion Matrix
 
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  sdk_version: 3.17.0
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  app_file: app.py
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  pinned: false
 
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  tags:
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  - evaluate
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  - metric
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  description: >-
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+ Compute confusion matrix to evaluate the accuracy of a classification. By definition a confusion matrix :math:C is such that :math:C_{i, j} is equal to the number of observations known to be in group :math:i and predicted to be in group :math:j.
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+ Thus in binary classification, the count of true negatives is :math:C_{0,0}, false negatives is :math:C_{1,0}, true positives is :math:C_{1,1} and false positives is :math:C_{0,1}.
 
 
 
 
 
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  ---
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  # Metric Card for Confusion Matrix