Home » Data Science » Machine Learning » True or False: When your data is missing at random, then whether or not you are missing a covariate is completely independent of your outcome. 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 A data analyst wants to find out how much the predicted outcome and the actual outcome of their data model differ. What function can they use to quickly measure this?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?Assume you have missing data on one of your features, and are considering two options: True or False: "Both options have the same performance".Fill in the blank: The _____ creates a scatterplot and then adds a small amount of random noise to each point in the plot to make the points easier to find.What function creates a scatterplot and then adds a small amount of random noise to each point in the plot to make the points easier to find?You’ve fit a random forest of 10 trees with max depth 20. Your training ROC is 0.99 and test ROC is 0.54. Which of the following is NOT a reasonable thing to try?True or False: If a > b, then ln(a) > ln(b).True or False: If t is larger than the longest survival time recorded in the dataset, then S(t) = 0S(t)=0 according to the Kaplan-Meier estimate.You train the random forest pictured below and it gets a c-index of 0.90. After shuffling the values for x, your dataset is the following. What is the variable importance for x?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…What is the C-index for a model which always outputs 0.6 for any patient regardless of their health outcome?You have created a model using mean imputation. At test time, you should fill in missing values with:Now assume that the hazards for patient 1, h_1and for patient 2, h_2 are proportional to each other. Also assume that S_1(T) > S_2(T) for some T > 0. Then which of the following is true about the…After reviewing your slide, you realize that the visual elements could be improved. A good solution would be for you to choose one data visualization to share on this slide, then create another slide…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