Home » Data Science » Machine Learning » Using regression imputation, and the decision tree shown here, what is your prediction for this person’s risk of heart attack? Q: Practice More Questions From: Prognosis With Tree-Based 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 Which decision boundary corresponds to the following decision tree? In the options, red indicates high risk, blue indicates low risk.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,…You are studying the effect of a new treatment for heart attack, your job consists in looking at outcomes of the effect in patients, fill the unit level treatment effect column using the Neyman-Rubin…Let’s say blood pressure (BP) measurements are more likely to be missing among young people, who generally have lower blood pressure. You use mean imputation to train your model. Which option…Say you have trained a decision tree which never splits on a variable X. What will be the variable importance for X using the permutation method?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?What is the hazard ratio between Person 1, a 40 year old non-smoker, and Person 2, a 30 year old smoker?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…One way to aggregate predictions from multiple trees is by a majority vote. Using this aggregation rule, select the prediction of the following trees on the data point (x=4, y=7, z=2):You have created a model using mean imputation. At test time, you should fill in missing values with:Using the S-Learner, or Single Tree, method, what is the conditional average treatment effect for a 61 year-old patient with a blood pressure (BP) of 140?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?Recall the MELD score from the lesson. What is the output for a person with Creatinine = 0.8 mg/dL, Bilirubin total = 1.5 mg/dL, INR = 1.3Calculate the conditional average treatment effect applying the Two-Tree Learner method, the patient has an Age=61 and BP= 130.True or False: A tree of depth 1 is more expressive than a classical linear model. Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 200+ Qs Machine Learning 100+ Qs