We typically break our datasets into two sets: training set and testing set. Whatis the purpose of the testing set?estimate the genrealization error of your model by simulating unseen datato act as additional data to further train your modelto perform hyperparameter tuning Measuring generalization error multiple times on the test set leads to a modelthat is biased to works best for ____. The solution to this problem is to use a newdata split referred to as the validation set which is used to evaluate theperformance of your model.O the train setall unseen dataall data drawn from the same distributionthe test set

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We typically break our datasets into two sets: training set and testing set. What is the purpose of the testing set? estimate the genrealization error of your model by simulating unseen data to act as additional data to further train your model to perform hyperparameter tuning

We typically break our datasets into two sets: training set and testing set. What is the purpose of the testing set? estimate the genrealization error of your model by simulating unseen data to act as additional data to further train your model to perform hyperparameter tuning

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

Problem 1PE

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Concept explainers

System Model Approaches

The systems model approach is a process-oriented representation that emphasizes the impact or flow of information between modules. The multidisciplinary study of the use of models to design and create systems in business and IT development is known as systems model approach. It models how processes interact and what these processes do, but it does not go into detail about how these processes are implemented. Functional decomposition may be utilized to enhance the models employed in this technique, and they can be coupled to requirements models for additional system partitioning.

Question

We typically break our datasets into two sets: training set and testing set. What
is the purpose of the testing set?
estimate the genrealization error of your model by simulating unseen data
to act as additional data to further train your model
to perform hyperparameter tuning

Measuring generalization error multiple times on the test set leads to a model
that is biased to works best for ____. The solution to this problem is to use a new
data split referred to as the validation set which is used to evaluate the
performance of your model.
O the train set
all unseen data
all data drawn from the same distribution
the test set

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