I need help answering these questions

Question 1:

b. Compute the misclassification rate, accuracy rate, sensitivity, precision, and specificity using the cutoff value of 0.25. (Round your final answers to 2 decimal places.) Misclassification rate Accuracy rate Sensitivity Precision Specificity c. Compute the misclassification rate, accuracy rate, sensitivity, precision, and specificity using the cutoff value of 0.75. (Round your final answers to 2 decimal places.) Misclassification rate Accuracy rate Sensitivity Precision SpecificityAnswer the following questions using the accompanying data set that lists the actual class memberships and predicted Class \"I {target class] probabilities for \"ID observations. EjpicturcCIick hero for the Excel Data File a. Compute the misclassication rate. accuracy rate, sensitivity. precision. and specificity using the cutoffvalue of 0.5. {Round your final answers to 2 decimal places} Misclassication rate Accu racy rate Sensitivity Precision Specificity \fCompute the RMSE, ME, MAD, MPE, and MAPE using the accompanying data set that lists the actual and predicted values for 10 observations. (Negative values should be indicated by a minus sign. Round intermediate calculations to at least 4 decimal places and your final answers to 2 decimal places.) ExpictureClick here for the Excel Data File RMSE ME MAD MPE MAPE\fc-2. Do the predictive models built by the real estate company outperform the base model in terms of RMSE? The predictive models the base model. d. Which predictive model is the better-performing model? is the better-performing model.b. Are the predictive models over- or underestimating the actual selling price on average? The predictive models the actual selling price. c-1. Compare the predictive models to a base model where every house is predicted to be sold at the average price of all the houses in the training data set, which is $260,500. Compute RMSE for the base model. (Round intermediate calculations to at least 4 decimal places and your final answer to 2 decimal places.) RMSEA real estate companvI has built two predictive models for estimating the selling price of a house. Using a small test data set of 10 observations. it tries to assess how the prediction models would perform on a new data set. The following table lists a portion of the actual prices and predicted prices generated by the two predictive models. Actual Predicted Predicted House Price Price 1 Price 2 1 $230,500 $ 254,000 $256,000 2 $209,900 $ 215,500 $223,400 10 $328,900 5 340,000 $324,500 EpictureCIick here for the Excel Data File a. Compute the ME, RMSE, MAD, MPE, and MAPE for the two predictive models. {Round intermediate calculations to at least 4 decimal places and your nal answers to 2 decimal places. Negative values should be indicated by a minus sign.) Hodal'l Medal! RMSE ME MAD MPE MAPE