Consider a classifier model in place which classifies emails as 'spam' and 'not-spam'. After a trial run on a test data-set consisting of 200 instances, the performance was evaluated based on the confusion matrix ( shown below) . The objective of the model is to correctly classify an email as SPAM. SPAM-Not-SPAM- Confusion Matrix

Spend some time to understand this confusion matrix in the context of the model mentioned above and answer the questions in the following questions -

What is the count of True Positives(TP) from the entire list of 200 ?


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