When using a training and testing set to finding a model that is a good fit to our data we are mplicitly: Select the correct answer) Simultaneously minimizing model bias and variance O Minimizing the model's prediction error on our training set O Discarding attributes from the data set O Discarding outliers from the data set

When using a training and testing set to finding a model that is a good fit to our data we are mplicitly: Select the correct answer) Simultaneously minimizing model bias and variance O Minimizing the model's prediction error on our training set O Discarding attributes from the data set O Discarding outliers from the data set

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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Do an analysis of a real data set and also mention where did you find the data set. Please do analysis completely in R studio. A basic requirement for the data set is that it includes one response variable and at least two predictor variables.The main objectives of this question are• to identify a suitable data set,• to come up with meaningful research questions based on the data,• to experience some of the problems encountered when analyzing real data,Also mention:• Where I find the data set?• Why the problem is of interest?• Which method or model is appropriate to this problem?• How do I apply the method to analysis the data set?• What is my conclusion?
What is true about a validation set? its data should be similar to that of the training set we train our models on the validation set to show that they are valid the validation set is often smaller than the training set validation sets, while popular, are not necessary to produce ML models to be used in the world the validation set is the collection of y-values to the inputs to your model, which are the x-values
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