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1) Determining if am email is Spam e-mail is an example of which of the following approaches of data mining? a

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1) Determining if am email is Spam e-mail is an example of which of the following approaches of data mining?

a. reduction

b. classification

c. regression

d. cause-and-effect modeling

 

2. Validation data sets differ from training data sets with in that validation data sets_____

a. provide the most realistic test for models with known data

b. are used to teach data mining algorithms

c. have known outcomes

d. are used to compare predicted values with original values

 

3. The____ of a regression analysis output will indicate, on average, how far off the outcome values generated by the regression coefficients are from the original observed y values

a. regression standard error

b. partial slope coefficients

c. individual t-test

d. p-value

 

4. _____ is a measure of the proportion of times a customer was classified as not a credit risk when the customer actually was credit risk

a. false

b. negative

 

5. Which of the following is true of a training data set?

a. They are used to build models where the data is unknowns

b. They have known outcomes

c. They are primarily used to fine-tune models

d. They provide the most realistic estimate for a model's performance

 

6. ______is a machine learning approach where labeled data is used to train the algorithm on how to recognize a pattern in data so that classification can be made for unclassified data

 

7. Which of the following regression analysis output will indicate the magnitude of impact of a person's income, age, years of education, and years of work experience on the value of that person's home?

a. r-squared

b. partial slope coefficient

c. standard error

d. individual t-test

 

8. A_____ has only knows predictors and no outcomes or labels are known and is used to make classifications using a validated algorithm

a. linear regression dataset

b. validation dataset

c. training dataset

d. text dataset

 

9. Which of the following is NOT true of K- means analysis?

a. The input data used must be numeric

b. you need to have an idea of how many groups might possibly be in the sample data

c. Can be used as a predict group membership using test data

d. Is an unsupervised machine learning algorithm

 

10.  _________is performed on data when the values of different variables are significantly different in magnitude from each other.

 

11.  Which of the following represents a classification algorithm's ability to identify a student that will likely graduate from college versus a student that will not graduate from college?

a. accurate

b. precision

c. true positive

d. recall

 

12.  _____ is a data mining technique that can be used to analyze several characteristics of hospital patients and their reaction to treatment so that they try to predict how a new patient might react to treatment.

a. data exploration

b. k-nearest Neighbor

c. k-means 

d. regression analysis

 

13. Which of the following regression analysis output will indicate how well the combined effect of a person's income, age, years of education, and years of work experience can provide a good prediction of the value of that person's home?

a. partial slope coefficient

b. r-squared

c. standard error

d. individual t-test