Question

Suppose you have created a classification model. Later you have evaluated the model with a confusion...

Suppose you have created a classification model. Later you have evaluated the model with a confusion matrix learned from class. The table below shows all four values from the test data:

TP:     10      9       8       8       6       5       5       4       3       3       1       0

FP:     10      10      9       8       8       8       6       6       5       2       2       0

FN:     0       1       2       2       4       5       5       6       7       7       9       10

TN:     0       0       1       2       2       2       4       4       5       8       8       10

1. Does this model, according to the ROC curve you have generated, make the prediction better than a random guess?

2. What is the highest value of accuracy this model has reached, according to this test data?

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