After training a classifier model we have produced following confusion matrix where Y = 1 corresponds to a 'positive' prediction. Predicted Y = 0 Predicted Y = 1 Actual Y = 0 60 Actual Y = 1 60 75 (a) Determine the Accuracy, Precision Recall and F1 Score of your model (it's ok to leave the solution in fractional form like 1/10) (b) Analyze your model's performance. In what ways does it perform well and in what ways does it under-perform? (c) Propose a specific way you could try and improve the model's performance, and discuss how that approach might impact the other metrics.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
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After training a classifier model we have produced following confusion matrix where Y = 1 corresponds to
a 'positive' prediction.
Predicted Y = 0 Predicted Y
1
Actual Y = 0
60
5
Actual Y = 1
60
75
(a) Determine the Accuracy, Precision Recall and F1 Score of your model (it's ok to leave the solution
in fractional form like 1/10)
(b) Analyze your model's performance. In what ways does it perform well and in what ways does it
under-perform?
(c) Propose a specific way you could try and improve the modelľ's performance, and discuss how that
approach might impact the other metrics.
Transcribed Image Text:After training a classifier model we have produced following confusion matrix where Y = 1 corresponds to a 'positive' prediction. Predicted Y = 0 Predicted Y 1 Actual Y = 0 60 5 Actual Y = 1 60 75 (a) Determine the Accuracy, Precision Recall and F1 Score of your model (it's ok to leave the solution in fractional form like 1/10) (b) Analyze your model's performance. In what ways does it perform well and in what ways does it under-perform? (c) Propose a specific way you could try and improve the modelľ's performance, and discuss how that approach might impact the other metrics.
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