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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-marke
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?
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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.
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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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