Question: Business Analytics and Decision Making 1. Describe what a parameter learning or parametric modeling is. 2. What is the Support vector machine (SVM) and how

Business Analytics and

Decision Making

1. Describe what a parameter learning or parametric modeling is. 2. What is the Support vector machine (SVM) and how is it used to fit the data? How does SVM differ from linear regression and logistic regression? 3. Consider the following logistic regression equation: In(estimated odds ratio of default=-2.25 +0.5X +0_2X a. Interpret the meaning of the logistic regression coefficients. b. If X-2 and X.-1.5, compute the estimated odds ratio and interpret its meaning. c. On the basis of the results of (b), compute the estimated probability of a default 2. Distinguish between supervised and unsupervised data mining problems. Give examples to cach. 3. Discuss in detail the steps involved in CRISP data mining process (NB: Cross Industry Standard Process for Data Mining - CRISP-DM)

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