Home » Data Science » Machine Learning » 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? Q: Practice More Questions From: Disease Detection With Computer Vision Created with Fabric.js 4.6.0 Similar Questions What code chunk do you add to the third line to save your plot as a png file with chocolate as the file name?Let’s say you have a relatively small training set (~5 thousand images). Which training strategy makes the most sense? 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?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 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 are working with the penguins dataset. You want to use the summarize() and mean() functions to find the mean value for the variable body_mass_g. You write the following code:penguins…You want to record and share every step of your analysis, let teammates run your code, and display your visualizations. What do you use to document your work?A data analyst writes the following code chunk to return a statistical summary of their dataset: quartet %>% group_by(set) %>% summarize(mean(x), sd(x), mean(y), sd(y), cor(x, y)) Which function will…Which of the following is not an example of a clinical application of a prognostic model?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?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.Use the following entry in SNOMED CT to help determine the positive labels for this x-ray report.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 want to use the summarize() and mean() functions to find the mean rating for your data. Add the code chunk that lets you find the mean value for the variable Rating. What is the mean rating?You want to use the summarize() and sd() functions to find the standard deviation of the rating for your data. Add the code chunk that lets you find the standard deviation for the variable Rating. Created with Fabric.js 4.6.0 Practice More Questions Data Analysis 200+ Qs Machine Learning 100+ Qs