Homework Answers
Regression problem is when we try to find out the relation between two sets of data We have a independent variable, x & an dependent variable y and through this analysis we can find an equation in the form of y=f(x), called a Linear Regression.
Example, the Employee salary in a Corporate, the output here will be real value or numeric.
Classification problem is when the output variable is category, the stock price of a Company will increase or decrease is catergorical.
15. The answer is A
16. The Answer is C - L2 Regularization
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15-For Regression problems, target variable is and for Classification, target variable is A) Numeric, Categorical B)...
5. a. Suppose that the target variable in a classification task is continuous numeric, can you...
5. a. Suppose that the target variable in a classification task is continuous numeric, can you apply decision trees directly to it? How can you work around this? 5 points b. Models A and B has an error rate of 15% and 25% respectively. Further, the AUC for models A and B respectively is 65% and 70%. Which of these models is better? 5 points c. Would you prefer more to less false positive or false negative in each following...
data as best as possible 17- Logistics regression with less regularization leads to fitting A) training...
data as best as possible 17- Logistics regression with less regularization leads to fitting A) training B) test C) training or test D) Both a and c 18- is the approach used to estimate the coefficients in a logistics regression A) Minimum Likelihood B) Maximum Likelihood C) Average likelihood D) Min-Max Likelihood A) In ( B) 1-prlu 19- Which choice shows the log-odds? A) In Pr(target vriable) (1-Pr(target vriable) B) Pr(target vriable) 1-Pr(target vriable) C) In (1-Pr(target vriable) Pr(target vriable)...
In regression analysis: a. the independent variable must be categorical in nature. b. the variables being...
In regression analysis: a. the independent variable must be categorical in nature. b. the variables being investigated must not be correlated. c. the independent variable is indisputably influenced by the dependent variable. d. one variable is believed to be influenced by the other.
7.3 Consider a set of three records with two numeric fields X, and Y. Type is the categorical tar...
7.3 Consider a set of three records with two numeric fields X, and Y. Type is the categorical target variable. Record X 3.0 3.0 3.0 3.0 Small Large Large (a) Suppose we have a new record (D) with values X-1.5 and Y-3.0. Use k-NN simple unweighted voting (for different values of k-1,2, and 3) to determine the classification of D. A scatter plot of Y against X shows the location of the three training records, and new unclassified record. 3.5...
b) 4 bits c) 12 bits ) 16 bits 12) mov al, 0101b; mov bl, 1100b;...
b) 4 bits c) 12 bits ) 16 bits 12) mov al, 0101b; mov bl, 1100b; and al, bl; What will AL be equal to after this code runs? b) 0xF3 c) 0x3F d) 0xF5 13) mov al, 0110b; mov bl, 1011b; or al, bl, xchg al, bl; neg al, What will AL and BL be equal to after this code runs? c) AL = 0xF3, BL = 0x1B 14) mov edx, 5 cmp edx, 10 ige L1, je L2...
Performance Metrics: Which of the following are terms used for performance metrics a. Specificity & Precision...
Performance Metrics: Which of the following are terms used for performance metrics a. Specificity & Precision b. Precision & Recall c. Recall & Sensitivity d. band e All of the above 9. Performance Metrics: When looking at the ROC/AUC curve, what are the values being compared represented on the x-axis and y-axis? a. False Positive Rate and True Positive Rate b. Precision and True Positive Rate c. False Positive Rate and Precision d. True Positive Rate and Specificity e. None...
Relevant costs for target pricing are ________. A) variable manufacturing costs B) variable manufacturing and variable...
Relevant costs for target pricing are ________. A) variable manufacturing costs B) variable manufacturing and variable nonmanufacturing costs C) all fixed costs D) all future costs, both variable and fixed
12. (Ch13.5) True or False? The effect of a binary predictor in a multiple regression with three ...
12. (Ch13.5) True or False? The effect of a binary predictor in a multiple regression with three predictors (two of them are continuous, one is binary) is to shift the regression fitting plane up or down 13. (Ch13.5) True or False? Unlike other predictors, the student's t for testing the significance of a binary predictor is either 0 or l1 14. (Ch13.5) In a multiple regression model of student grades, we would code the nine categories of business courses taken...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B,...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B, unbiased estimators for the B, (b) Explain how one can test the hypothesis that A +As = 0 by means of a t-test. (c) Explain how one can test the hypothesis that A-A-0. Indicate the relevant test statistic. (d) Suppose that ri is an irrelevant explanatory variable in the population model and that you estimate the model including both and r2. What are the...
Utolbl 5 2) (15 points) You have obtainer male students (Student a binary variable (Female), which...
Utolbl 5 2) (15 points) You have obtainer male students (Student a binary variable (Female), which yields the following result: ints) You have obtained measurements of height in inches of 29 female and 81 dents (Studenth) at your university. A regression of the height on a constant and variable (Female), which takes a value of one for females and is zero otherwise, Studenth = 71.0 - 4.84xFemale, R2 = 0.40, SER = 2.0 (0.3) (0.57) (a) Calculate the average height...
5. a. Suppose that the target variable in a classification task is continuous numeric, can you apply decision trees directly to it? How can you work around this? 5 points b. Models A and B has an error rate of 15% and 25% respectively. Further, the AUC for models A and B respectively is 65% and 70%. Which of these models is better? 5 points c. Would you prefer more to less false positive or false negative in each following...
data as best as possible 17- Logistics regression with less regularization leads to fitting A) training B) test C) training or test D) Both a and c 18- is the approach used to estimate the coefficients in a logistics regression A) Minimum Likelihood B) Maximum Likelihood C) Average likelihood D) Min-Max Likelihood A) In ( B) 1-prlu 19- Which choice shows the log-odds? A) In Pr(target vriable) (1-Pr(target vriable) B) Pr(target vriable) 1-Pr(target vriable) C) In (1-Pr(target vriable) Pr(target vriable)...
7.3 Consider a set of three records with two numeric fields X, and Y. Type is the categorical target variable. Record X 3.0 3.0 3.0 3.0 Small Large Large (a) Suppose we have a new record (D) with values X-1.5 and Y-3.0. Use k-NN simple unweighted voting (for different values of k-1,2, and 3) to determine the classification of D. A scatter plot of Y against X shows the location of the three training records, and new unclassified record. 3.5...
b) 4 bits c) 12 bits ) 16 bits 12) mov al, 0101b; mov bl, 1100b; and al, bl; What will AL be equal to after this code runs? b) 0xF3 c) 0x3F d) 0xF5 13) mov al, 0110b; mov bl, 1011b; or al, bl, xchg al, bl; neg al, What will AL and BL be equal to after this code runs? c) AL = 0xF3, BL = 0x1B 14) mov edx, 5 cmp edx, 10 ige L1, je L2...
Performance Metrics: Which of the following are terms used for performance metrics a. Specificity & Precision b. Precision & Recall c. Recall & Sensitivity d. band e All of the above 9. Performance Metrics: When looking at the ROC/AUC curve, what are the values being compared represented on the x-axis and y-axis? a. False Positive Rate and True Positive Rate b. Precision and True Positive Rate c. False Positive Rate and Precision d. True Positive Rate and Specificity e. None...
12. (Ch13.5) True or False? The effect of a binary predictor in a multiple regression with three predictors (two of them are continuous, one is binary) is to shift the regression fitting plane up or down 13. (Ch13.5) True or False? Unlike other predictors, the student's t for testing the significance of a binary predictor is either 0 or l1 14. (Ch13.5) In a multiple regression model of student grades, we would code the nine categories of business courses taken...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B, unbiased estimators for the B, (b) Explain how one can test the hypothesis that A +As = 0 by means of a t-test. (c) Explain how one can test the hypothesis that A-A-0. Indicate the relevant test statistic. (d) Suppose that ri is an irrelevant explanatory variable in the population model and that you estimate the model including both and r2. What are the...
Utolbl 5 2) (15 points) You have obtainer male students (Student a binary variable (Female), which yields the following result: ints) You have obtained measurements of height in inches of 29 female and 81 dents (Studenth) at your university. A regression of the height on a constant and variable (Female), which takes a value of one for females and is zero otherwise, Studenth = 71.0 - 4.84xFemale, R2 = 0.40, SER = 2.0 (0.3) (0.57) (a) Calculate the average height...
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