Answer: Individually R squared cannot tell about variable importance. We can’t say anything about it right now
Answer: Individually R squared cannot tell about variable importance. We can’t say anything about it right now
Answer: Mean of residuals is always zero
Article and Schedule Quiz | Start Test! |
Answer: Linear Regression with varying error terms
Answer: The strength of the relationship between the x and y variables
Answer: We need to fit n model in n-class classification problem
Answer: Sigmoid
Answer: Lasso
Answer: Scatter plot
Answer: Correlation coefficient = 0.9
1. Linear Regression 2. Logistic Regression
Answer: only 1
1. Simple Linear regression will have high bias and low variance 2. Simple Linear regression will have low bias and high variance 3. polynomial of degree 3 will have low bias and high variance 4. Polynomial of degree 3 will have low bias and Low variance
Answer: 1 and 4
Answer: It is more likely for X1 to be included in the model
Answer: Lasso regression uses subset selection of features
1. R-Squared and Adjusted R-squared both increase 2. R-Squared increases and Adjusted R-squared decreases 3. R-Squared decreases and Adjusted R-squared decreases 4. R-Squared decreases and Adjusted R-squared increases
Answer: 1 and 2
Answer: The relationship is symmetric between x and y in case of correlation but in case of regression it is not symmetric
Answer: In case of very large lambda; bias is high, variance is low
Answer: In case of very small lambda; bias is low, variance is high
Answer: By its Slope
Answer: Both will be same
Answer: much smaller than 0, if the correlation is negative