7. (Random Questions) Answer each o f the following questions in at most two brief sentences. (a) Why do we expect predictive models with less features to be more generalizable? (b) In training a classifier, after we divide the samples into a training set and a test set, we often further divide the training set into a training set used for model building and a validation set. What purpose does the validation set serve? (c) Assume that we have 100 samples and we are using 5-fold cross validation. How many different models will be built? How many training samples will be used to train each model?

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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7.
(Random Questions) Answer each o f the following questions in at most two brief
sentences.
(a) Why do we expect predictive models with less features to be more generalizable?
(b) In training a classifier, after we divide the samples into a training set and a test set, we often
further divide the training set into a training set used for model building and a validation set.
What purpose does the validation set serve?
(c) Assume that we have 100 samples and we are using 5-fold cross validation. How many
different models will be built? How many training samples will be used to train each model?
Transcribed Image Text:7. (Random Questions) Answer each o f the following questions in at most two brief sentences. (a) Why do we expect predictive models with less features to be more generalizable? (b) In training a classifier, after we divide the samples into a training set and a test set, we often further divide the training set into a training set used for model building and a validation set. What purpose does the validation set serve? (c) Assume that we have 100 samples and we are using 5-fold cross validation. How many different models will be built? How many training samples will be used to train each model?
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