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…Compute the probability of surviving up to 4 years S(4)S(4) given the following dataset using the Kaplan Meier estimate: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?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
