A. Please define the following terms as accurately, clearly, and concisely as possible. (40 points)
a. Data Mining
b. Data Mining Algorithm
c. Machine Learning
d. Supervised Learning
e. Unsupervised Learning
f. Model (in data mining domain)
g. Response
h. Overfitting

B. Please list all supervised learning algorithms you know (15 points)

C. Please list all unsupervised learning algorithms you know (15 points)

D. Given two models applied to a data set that has been partitioned, Model A is considerably more accurate than model B on the training data, but slightly less accurate than model B on validation data.

a. Which model are you more likely to consider for final deployment? (10 points)
b. Please explain why “Model A is considerably more accurate than model B on the training data, but slightly less accurate than model B on validation data” as concise as possible. (10 points)

E. In order to achieve a given degree of reliability with a given dataset and a given model, for a classification procedure, what is the good ratio between the number of records and predictor variables? (10 points)