Section 5. Programming Question on Decision Trees (Questions…

Section 5. Programming Question on Decision Trees (Questions 17-22) Suppose you are asked to predict if a student will be accepted or rejected from the University of Data Science. For this task, you will be working with the Students dataset, containing a binary outcome ‘Accepted’ of 19 students. There are 5 predictors including ‘GPA’, ‘SAT Math Score’, ‘SAT Reading Score’, ‘Sex’, and ‘State’. You may assume that the following import statements have already been included: import pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport graphvizimport seaborn as snsfrom IPython.display import Imageimport pydotplusfrom sklearn import tree The first thing we need to do is read in the dataset with the following code: students = pd.read_csv(‘Students.csv’) students.head()  What output would you expect to see?

The following is classified as a β-lactam antimicrobial agen…

The following is classified as a β-lactam antimicrobial agent:                                                                                      1.           Glycopeptides2.           Lincosamides3.           Macrolides4.           Aminoglycosides5.           Cephalosporins

The following drug is most effective in improving High densi…

The following drug is most effective in improving High density lipoprotein levels:                                                    1.            Fluvastatin2.            Gemfibrozil3.            Cholestyramine 4.            Acipimox5.            Eicosapentaenoic acid

Section 4. Decision Trees (Questions 10-16) Consider the one…

Section 4. Decision Trees (Questions 10-16) Consider the one-dimensional (i.e., = 1) training dataset in the figure below (left side, red dots represent data pairs ).   Find the regression tree with two leaves having the smallest training MSE. What is the threshold value

The following can be used in the treatment of gout:         …

The following can be used in the treatment of gout:                                                                                                       1.            Warfarin2.            Phenytoin3.            Probenecid4.            Furosemide5.            Rifampicin

Section 7. Support Vector Machines (Questions 28-31) Conside…

Section 7. Support Vector Machines (Questions 28-31) Consider a dataset with points and two classes (red and blue) indicated in the figure below. (Note that (0, 0) and (1, 1) are blue points whereas (1, 0) and (0, 1) are red points).   Is the dataset linearly separable?

Regarding penicillins:                                      …

Regarding penicillins:                                                                                                                                                     1.            Are bacteriostatic2.           Are all completely absorbed when administered orally 3.           An example is trimethoprim4.           Are largely administered topically5.           Are cell wall synthesis inhibitors