Home » Data Science » Machine Learning » 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? 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 You are working with the penguins dataset. You want to use the summarize() and max() functions to find the maximum value for the variable flipper_length_mm. You write the following code:penguins…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?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 find that your training set has 70% negative examples and 30% positive. Which of the following techniques will NOT help for training this imbalanced dataset?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.Let’s say you have a relatively small training set (~5 thousand images). Which training strategy makes the most sense? You are working with the penguins dataset. You want to use the summarize() and min() functions to find the minimum value for the variable bill_depth_mm. You write the following code:penguins…You want to use the summarize() and max() functions to find the maximum rating for your data. Add the code chunk that lets you find the maximum value for the variable Rating. What is the maximum…A data analyst is working with a large data frame. It contains so many columns that they don’t all fit on the screen at once. The analyst wants a quick list of all of the column names to get a better…In what order should the training, validation, and test sets be sampled?Why is it bad to have the same patients in both training and test sets?True or False: A tree of depth 1 is more expressive than a classical linear model.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…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?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. Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 200+ Qs Machine Learning 100+ Qs