Home » Data Science » Machine Learning » What is the sensitivity and specificity of a model which randomly assigns a score between 0 and 1 to each example (with equal probability) if we use a threshold of 0.7? Q: Practice More Questions From: Evaluating Machine Learning Models Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 2000+ Qs Machine Learning 1000+ Qs Created with Fabric.js 4.6.0 Similar Questions For every specificity, as we vary the threshold, the sensitivity of model 1 is at least as high as model 2. Which of the following must be true?You have a model such that the lowest score for a positive example is higher than the maximum score for a negative example. What is its ROC AUC?Model 1 has a c-index of 0.7 and Model 2 has a c-index of 0.6. Which is more accurate using a threshold of 0.5 for the risk score?What is the sensitivity and specificity of a pneumonia model that always outputs positive? In other words, the models says that every patient has the disease.If sensitivity = 0.9, specificity = 0.8, and prevalence = 0.2, then what is the accuracy?In some studies, you may have to compute the Positive predictive value (PPV) from the sensitivity, specificity and prevalence.Person 1 has hazard h_1(t) = 1, and Person 2 has hazard h_2(t) = 2. What is the probability of dying within the first year for each patient?Let f(x) be the probability that a person with feature x dies within 5 years. Let Sx(t) be the survival function of a person with feature x. Assume t is measured in years. Which of the following is…A data analyst uses the bias() function to compare the actual outcome with the predicted outcome to determine if the model is biased. They get a score of 0.8. What does this mean?Compute the probability of surviving up to 4 years S(4)S(4) given the following dataset using the Kaplan Meier estimate:What is the MAIN disadvantage of processing each MRI slice independently using a 2D segmentation model (as mentioned in the lecture)?Which of the following is not an example of a clinical application of a prognostic model?A linear risk model for the risk of heart attack has three inputs: Age, Systolic Blood Pressure (BP), and the interaction term between Age and Systolic Blood Pressure. The coefficients for Age, BP,…We have the following table the output of a model f on an example using subsets of the variable. What is the sum of the Shapley value for s_BP and d_BP? We have the following table the output of a model f on an example using subsets of the variable. What is the Shapley value for s_BP? Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 200+ Qs Machine Learning 100+ Qs