An AI model made the following sales prediction for a new mobile phone which theyhave recently launched:Confusion MatrixRealityYes NoPredictionYes 50 40No 12 10(i) Identify the total number of wrong predictions made by the model.(ii) Calculate precision, recall and F1 Score

Given the confusion matrix for a disease prediction model, calculate the Precision, Recall, and F1-Score, and choose the correct values from the options below.1 pointPrecision: 0.800, Recall: 0.750, F1-Score: 0.774Precision: 0.778, Recall: 0.700, F1-Score: 0.737Precision: 0.850, Recall: 0.600, F1-Score: 0.706Precision: 0.900, Recall: 0.650, F1-Score: 0.756

Consider a classification problem with three classes: A, B, and C. A machine learning model is trained on a labeled dataset, and the confusion matrix for the model's predictions is given below:What is the overall accuracy of the model?a)0.69b)0.85c)0.8d)0.725

Which of the following models will you choose for forecasting the sales of the mobile phone?Model 1 with RMSE 2.33e+02Model 2 with RMSE 0.235e+03Model 3 with RMSE 2.32+e03Model 4 with RMSE 2.33e+05Answer choicesSelect only one optionREVISITModel 3Model 2Model 1Model 4

For the given confusion matrix, compute the recall True Positive True NegativePredicted Positive 8 3Predicted Negative 2 7 0.73 0.7 0.78 0.8

48.Consider a model that predicts 150 examples for the positive class, 95 are correct (true positives), meaning five were missed (false negatives) and 55 are incorrect (false positives). What will be the precision?  A. 55/150  B. 95/150  C. 55/95  D. 150/55