Question

Suppose you have fitted a
complex regression model on a
dataset. Now, you are using Ridge
regression with tuning parameter
lambda to reduce its complexity.
Choose the option(s) below which
describes relationship of bias and
variance with lambda.​

Answer 1

Answer:

sorry don't know sorry don't have a idea

Answer 2

Answer:

in the case of very large lambda; bias is high, variance is low

Explanation:

• If lambda is very large it means the model is less complex.
• So in this case bias is high and variance is low.

Variance: Variability is measured by the variance. The average of the squared deviations from the mean is used to compute it. The degree of dispersion in your data collection is indicated by variance. The variance is greater with respect to the mean when the data are more dispersed.

Statistical Bias: Anything that causes a systematic discrepancy between the statistics used to estimate a population's real parameters and those statistics themselves is considered to constitute statistical bias.

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