What is Precision Recall F1 score | Data Science Interview Questions and Answers | Thinking Neuron

https://thinkingneuron.com/data-scien... How many correct predictions were done for a class out of all predictions for that class? Precision for ‘Yes’ class will tell out of all the ‘Yes’ predicted by the algorithm, how many were correct? Similarly, Precision for ‘No’ class will tell out of all the ‘No’ predicted by the algorithm, how many were correct? i.e how precise the prediction is for that class. A Good range for precision is 0.7-0.9 ############################ How many actual values were correctly recalled by the model? In other terms, how many predictions were correct out of all the original values for that class. Recall for ‘Yes’ will tell out of all the Actual ‘Yes’ values how many were correctly predicted by the model. Recall for ‘No’ will tell out of all the Actual ‘No’ values how many were correctly predicted by the model. A good range for the recall is 0.7-0.9. ####################### F1-Score is the harmonic mean of Precision and recall. It is the accuracy of classification predictive model. It tells how efficient the model is while predicting Yes as Yes and No as No. A good range for F1-Score is 0.7-0.9