COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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all the data collected
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test the accuracy of your model
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learning new and different skills
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training a computer to recognize specific data
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Detailed explanation-1: -The three main metrics used to evaluate a classification model are accuracy, precision, and recall. Accuracy is defined as the percentage of correct predictions for the test data. It can be calculated easily by dividing the number of correct predictions by the number of total predictions.
Detailed explanation-2: -We calculate accuracy by dividing the number of correct predictions (the corresponding diagonal in the matrix) by the total number of samples. The result tells us that our model achieved a 44% accuracy on this multiclass problem.
Detailed explanation-3: -What is model accuracy? Model accuracy is defined as the number of classifications a model correctly predicts divided by the total number of predictions made. It’s a way of assessing the performance of a model, but certainly not the only way.