1. Implement and plot a simple linear regression for the above data, where the temperature is “x", and the length is “y" 2. Implement and plot a multiple linear regression "Polynomial regression" with different degrees. For example, Degree of 3:

1. Implement and plot a simple linear regression for the above data, where the temperature is “x", and the length is “y" 2. Implement and plot a multiple linear regression "Polynomial regression" with different degrees. For example, Degree of 3:

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

Decision Tree

A decision tree is a unique kind of probability tree. A popular and powerful tool used for prediction and classification. The decision tree structure is the same as a flowchart with a tree structure. The internal node refers to the attribute test, the branch refers to the outcome of the test, and the leaf node(terminal) contains the class label.

Question

We all know that when the temperature of a metal increases, it begins to expand. So,
we experimented with exposing a metal rod to different temperatures and recorded its
length as follows:
20
Length
Temp
25
30
35
40
45
50
55
60
65
0.5
1.8
5
6.2
6.5
7.8
9.4
9.8
10.9
Required:
1. Implement and plot a simple linear regression for the above data, where the
temperature is “x", and the length is "y"
2. Implement and plot a multiple linear regression "Polynomial regression" with
different degrees.
For example, Degree of 3:
Y = w,x' + w2x? + W3x³ + W4
Where w4 represents bias.
*you can use normal equation to calculate 'W' as follow:
W (X".X)².(X".Y)
Then calculate Y, Where Y = X.WT
3. Try degree of 2, 3, 5, and 8

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