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Fit a predictive linear regression model to estimate weight of the fish from its length, height and width?

Q1. Fit a predictive linear regression model to estimate weight of the fish from its length, height and width? (The data source fish.csv can be found here: https://www.kaggle.com/aungpyaeap/fish-market) (50 points)

-Report the coefficients values by using the standard Least Square Estimates

-What is the standard error of the estimated coefficients, R-squared term, and the 95% confidence interval?

-Is there any dependence between the length and weight of the fish?

Ans:

Q2. Using the data source in Q1 fit the Ridge and Lasso Regression Models.                                                                                                                                    (25 points)

–        Report the coefficients for both the models

–        Report the attribute(s) least impacting the weight of the fish.

Ans:

Q3. Modify the example code for Logistic Regression to include all the four attributes in iris dataset for two class and multi-class classification. Report any difference in the performance if noted.                                                                                                                                  (25 points)

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How does prescriptive analytics relate to descriptive and predictive analytics?

1. How does prescriptive analytics relate to descriptive and predictive analytics?

2. Explain the differences between static and dynamic models. How can one evolve into the other?

3. What is the difference between an optimistic approach and a pessimistic approach to decision making under assumed uncertainty?

4. Explain why solving problems under uncertainty some-times involves assuming that the problem is to be solved under conditions of risk.

5. Investigate via a Web search how models and their solutions are used by the U.S. Department of Homeland Security in the “war against terrorism.” Also investigate how other governments or government agencies are using models in their missions.

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