In a dataset, there are 1000 samples from apples and oranges. The dataset is split into two parts as 90% and 10% for training and testing, respectively. In the testing data, there are equal numbers of for apples and oranges. A supervised machine learning algorithm is trained to detect apples and oranges using the training dataset. When it is tested with the testing data, it finds the following results: Answer with an integer, no spaces. • It classifies 5 apples as oranges. • It classifies 40 oranges as oranges. Fill out the confusion matrix for the given information above: Model 1 Predicted Class Apple (+) Apple (+) Actual Class Oranges (-) C What are the a, b, c, d values in the confusion matrix? a: ? b: ? a:? d:? a Oranges (-) b d

In a dataset, there are 1000 samples from apples and oranges. The dataset is split into two parts as 90% and 10% for training and testing, respectively. In the testing data, there are equal numbers of for apples and oranges. A supervised machine learning algorithm is trained to detect apples and oranges using the training dataset. When it is tested with the testing data, it finds the following results: Answer with an integer, no spaces. • It classifies 5 apples as oranges. • It classifies 40 oranges as oranges. Fill out the confusion matrix for the given information above: Model 1 Predicted Class Apple (+) Apple (+) Actual Class Oranges (-) C What are the a, b, c, d values in the confusion matrix? a: ? b: ? a:? d:? a Oranges (-) b d