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In a couple of sentences, elaborate what each concept mean in terms of statistical learning and data mining: a. variance of an estimator, b. bias of an estimator, c. the difference between prediction and confidence intervals, d. model complexity, e. the difference between training and testing error, f. the differences between the KNN classifier and KNN regression methods.

In a couple of sentences, elaborate what each concept mean in terms of statistical learning and data mining: a. variance of an estimator, b. bias of an estimator, c. the difference between prediction and confidence intervals, d. model complexity, e. the difference between training and testing error, f. the differences between the KNN classifier and KNN regression methods.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 4GP
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In a couple of sentences, elaborate what each concept mean in terms of statistical learning and data mining: a. variance of an estimator, b. bias of an estimator, c. the difference between prediction and confidence intervals, d. model complexity, e. the difference between training and testing error, f. the differences between the KNN classifier and KNN regression methods.
Transcribed Image Text:In a couple of sentences, elaborate what each concept mean in terms of statistical learning and data mining: a. variance of an estimator, b. bias of an estimator, c. the difference between prediction and confidence intervals, d. model complexity, e. the difference between training and testing error, f. the differences between the KNN classifier and KNN regression methods.
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