Our Services

Get 15% Discount on your First Order

[rank_math_breadcrumb]

data science

Assignment 4
Due Saturday 11:59 pm (Week 10)

In this assignment, you will be required to do research about Decision tree Regressor
and other common regressions such as Ridge Regression, Lasso Regression, and Logistic
Regression.

Like Assignment 3, you will need to do the research about these regression models, but
you don’t need to find their mathematical formulas. You are only required to know what
they are, how and when to use them.
1. Research (20 points)

You will need to find the answers for the following questions in order to help you
understand how these regressions work. Write your answers for each question in
your write-ups.
• What is Decision tree Regressor?
• What is the difference between Decision Tree Regressor and Decision Tree

Classifier.
• What is the feature importance in Decision Tree Regressor?
• What is Ridge Regression?
• What is Lasso Regression?
• What is Logistic Regression?

2. Use the Boston housing data again (Assignment 2). Since we have done EDA of this

dataset in assignment 2, it will save us a lot of time so that we can focus on applying
each regression that we discussed above. (50 points, each regression counts as 10
points.)
• For Linear Regression, Ridge Regression, Lass Regression, and Logistic

Regression, find the correlations for all the independent variables and
dependent variables. Select the feature variables that correlate to the price of
the house. (To use the logistics model, you may have to separate the price of the
house into low, medium, and high).
For Decision Tree Regressor, we will use all features to predict the price of the
Boston house price.

• Apply Linear Regression, Ridge Regression, Lass Regression, Logistic Regression,
and Decision Tree Regressor to the data. Your assignment should have at least 5
models.

• Comparing the MSE, RMSE, and its accuracies.
• Choose the model(s) that you think appropriate and predict the house price.

• Only for Decision Tree Regressor, do the tree visualization, and plot the feature
importance, find which feature has the highest importance, and which feature is
the second highest importance.

• Interpret the results.

General Requirements for all your assignments.

You will need to write up your findings, interpretations, and results (30 points) for this
assignment. Use the Machine Learning Workflow of Week 6 as a guideline for your
assignment. It will be a great idea to screenshot your codes, results, and graphs so that
you can explain your findings along with them. (It is also easier for me to follow you
when I read your paper). A pdf file is required. There is no page limit but try to be
straightforward with your answers.

The py file that you have used to finish your assignment. (It may be a duplicate or
somewhat duplicate of the screenshots that you have inserted in your paper but that is
okay. I would like to look over your codes.)

Share This Post

Email
WhatsApp
Facebook
Twitter
LinkedIn
Pinterest
Reddit

Order a Similar Paper and get 15% Discount on your First Order

Related Questions

Computer Science 2 Assignments

Operational Excellence Week 2 Assignment Information Systems for Business and Beyond Questions: · Chapter 3 – study questions 1-8, Exercise 2, 4 & 5 Information Technology and Organizational Learning Assignment: Chapter 3 – Complete the two essay assignments noted below:  · Review the strategic integration section.  Note what strategic integration is and how

Discussion 3: generative adversarial nets

  Generative adversarial nets are mentioned in 2014 by Ian Goodfellow et al.  Why is generative adversarial network a key turning point in the history of generative modeling? Why is the field of image generation important? 

Week 3 – Linear Regression & Business Decision Making

attached file.  An asset management company must replace the manager of its two signature mutual funds, who is about to retire. Two candidates have been short-listed. The management team is divided and cannot decide which of the two candidates would make the better mutual fund manager. The retiring manager presents

data science

Final Exam Due Saturday 11:59 pm (Week 15) You cannot use any of the datasets in our assignments, class notes, and your own midterm project. If you are using the same one, you will receive 0 for your final project. 1. Question Formulation (5 points): You need to devise a

Letter of Recommendations

Hi  Attached is the sample of Letter of recommendation  Please write about it accordingly  1. Write about author :AUTHOR WILL BE professor David Kimble I will give links about his Biography write accordingly or you can use your own search engines about him to write it. 2 . How the

Letter of Recommendations

Hi  Attached is the sample of Letter of recommendation  Please write about it accordingly  1. Write about author :AUTHOR WILL BE professor David Kimble I will give links about his Biography write accordingly or you can use your own search engines about him to write it. 2 . How the

data science

Final Exam Due Saturday 11:59 pm (Week 15) You cannot use any of the datasets in our assignments, class notes, and your own midterm project. If you are using the same one, you will receive 0 for your final project. 1. Question Formulation (5 points): You need to devise a

IT 202

5/15/24, 10:59 AM Assignment Information 1/3 IT 202 Project One Milestone Guidelines and Rubric Overview For the purposes of this assignment, imagine that you are a systems architect at a medium-sized publishing company with 130 employees. The company primarily publishes books, both in print and online. It also produces other

Assessments

Perimeter defense techniques Evaluate the types of assessments, select one that you might use, and explain why it is important. Of the top eight areas to research when conducting an assessment, select no less than three and explain how one should approach the research and why it should be approached

project ppt presentation

Project 3 – Ensemble Methods and Unsupervised Learning In this project you will explore some techniques in unsupervised learning as well as ensemble methods. It is important to realize that understanding an algorithm or technique requires understanding how it behaves under a variety of circumstances. You will go through the

Week 2 understanding on Python.

PDF for reference purpose other file is requirement Python Installation & Examples Atif Farid Mohammad PhD 1. Open any Browser 2. Go to 3. Click at Download button 4. Go to your Download Folder (In both Windows and Mac) a. In Windows you will have the file: Anaconda3-2022.05-Windows-x86_64.exe b. Double

Computer Science Assignments

Operational Excellence Week 2 Assignment information Systems for Business and Beyond Questions · Chapter 2 – study questions 1-10, Exercise 2      Information Technology and Organizational Learning Questions · Chapter 2 – Note why the IT organizational structure is an important concept to understand.  Also, note the role of

Computer Science IT project assignment

Pg. 01 Project I Project Deadline: Sunday 12/5/2024 @ 23:59 [Total Mark is 14] Introduction to Database IT244 College of Computing and Informatics Project Instructions · You can work on this project as a group (minimum 2 and maximum 3 students). Each group member must submit the project individually with

project ppt presentation

Project 3 – Ensemble Methods and Unsupervised Learning In this project you will explore some techniques in unsupervised learning as well as ensemble methods. It is important to realize that understanding an algorithm or technique requires understanding how it behaves under a variety of circumstances. You will go through the

coding

Assignment 6 Due Saturday 11:59 pm (Week 14) Part 1 (50 points) We will explore the Marvel Network Universe. The dataset which you will find in Blackboard consists of the hero’s networks. For this dataset, you will need to ask yourself 3 questions (i.e which superhero knows more superheroes?) ,

project ppt presentation

Project 3 – Ensemble Methods and Unsupervised Learning In this project you will explore some techniques in unsupervised learning as well as ensemble methods. It is important to realize that understanding an algorithm or technique requires understanding how it behaves under a variety of circumstances. You will go through the

How hackers get info

Identify at least two ways in which hackers gather information about companies. What can companies do to limit this access, specifically to the ways you have identified? Which type of information can be gathered with enumeration? How and why should companies protect themselves against enumeration attempts?