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# 02450students
# 02450 Introduction to Machine Learning and Data Mining
## Purpose
The content of this repository is intended for students enrolled on course 02450 Introduction to machine learning and data mining at
the Technical University of Denmark (DTU).
Official course description: https://kurser.dtu.dk/course/02450
## Getting started
Public webpage for 02450: https://www2.imm.dtu.dk/courses/02450/
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
## Content
- [ ] Exercise toolbox/scripts: The toolbox is available in this repository in R, Matlab and Python. Follow the installation instructions in the individual folder and the exercise instructions (available via DTU Learn).
- [ ] Exercise instructions: The instructions for the exercises are only available via DTU Learn available to enrolled students.
- [ ] Book: The book is currenlty only available in pdf format for enrolled students via DTU Learn. A hardcopy can be purchased via the Polyteknisk bookstore at DTU.
## Add your files
## Licensing
See individual foldes/files. The content is not for redistrbution.
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
```
cd existing_repo
git remote add origin https://lab.compute.dtu.dk/02450/02450students.git
git branch -M main
git push -uf origin main
```
## Integrate with your tools
- [ ] [Set up project integrations](https://lab.compute.dtu.dk/02450/02450students/-/settings/integrations)
## Collaborate with your team
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Test and Deploy
Use the built-in continuous integration in GitLab.
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
***
# Editing this README
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
## Name
Choose a self-explaining name for your project.
## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
## Badges
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
## Visuals
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
## Support
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
## Roadmap
If you have ideas for releases in the future, it is a good idea to list them in the README.
## Contributing
State if you are open to contributions and what your requirements are for accepting them.
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
## Authors and acknowledgment
Show your appreciation to those who have contributed to the project.
## License
For open source projects, say how it is licensed.
## Project status
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
# 02450 Book
The book is currently only available for student enrolled on the course via DTU Learn.
\ No newline at end of file
File added
2,5,6,7,8
1,2,3,6,7,8
2,4,6,8
3,6,7
2,6,7
2,3,6,7,8
File added
File added
3.600000 79.000000
1.800000 54.000000
3.333000 74.000000
2.283000 62.000000
4.533000 85.000000
2.883000 55.000000
4.700000 88.000000
3.600000 85.000000
1.950000 51.000000
4.350000 85.000000
1.833000 54.000000
3.917000 84.000000
4.200000 78.000000
1.750000 47.000000
4.700000 83.000000
2.167000 52.000000
1.750000 62.000000
4.800000 84.000000
1.600000 52.000000
4.250000 79.000000
1.800000 51.000000
1.750000 47.000000
3.450000 78.000000
3.067000 69.000000
4.533000 74.000000
3.600000 83.000000
1.967000 55.000000
4.083000 76.000000
3.850000 78.000000
4.433000 79.000000
4.300000 73.000000
4.467000 77.000000
3.367000 66.000000
4.033000 80.000000
3.833000 74.000000
2.017000 52.000000
1.867000 48.000000
4.833000 80.000000
1.833000 59.000000
4.783000 90.000000
4.350000 80.000000
1.883000 58.000000
4.567000 84.000000
1.750000 58.000000
4.533000 73.000000
3.317000 83.000000
3.833000 64.000000
2.100000 53.000000
4.633000 82.000000
2.000000 59.000000
4.800000 75.000000
4.716000 90.000000
1.833000 54.000000
4.833000 80.000000
1.733000 54.000000
4.883000 83.000000
3.717000 71.000000
1.667000 64.000000
4.567000 77.000000
4.317000 81.000000
2.233000 59.000000
4.500000 84.000000
1.750000 48.000000
4.800000 82.000000
1.817000 60.000000
4.400000 92.000000
4.167000 78.000000
4.700000 78.000000
2.067000 65.000000
4.700000 73.000000
4.033000 82.000000
1.967000 56.000000
4.500000 79.000000
4.000000 71.000000
1.983000 62.000000
5.067000 76.000000
2.017000 60.000000
4.567000 78.000000
3.883000 76.000000
3.600000 83.000000
4.133000 75.000000
4.333000 82.000000
4.100000 70.000000
2.633000 65.000000
4.067000 73.000000
4.933000 88.000000
3.950000 76.000000
4.517000 80.000000
2.167000 48.000000
4.000000 86.000000
2.200000 60.000000
4.333000 90.000000
1.867000 50.000000
4.817000 78.000000
1.833000 63.000000
4.300000 72.000000
4.667000 84.000000
3.750000 75.000000
1.867000 51.000000
4.900000 82.000000
2.483000 62.000000
4.367000 88.000000
2.100000 49.000000
4.500000 83.000000
4.050000 81.000000
1.867000 47.000000
4.700000 84.000000
1.783000 52.000000
4.850000 86.000000
3.683000 81.000000
4.733000 75.000000
2.300000 59.000000
4.900000 89.000000
4.417000 79.000000
1.700000 59.000000
4.633000 81.000000
2.317000 50.000000
4.600000 85.000000
1.817000 59.000000
4.417000 87.000000
2.617000 53.000000
4.067000 69.000000
4.250000 77.000000
1.967000 56.000000
4.600000 88.000000
3.767000 81.000000
1.917000 45.000000
4.500000 82.000000
2.267000 55.000000
4.650000 90.000000
1.867000 45.000000
4.167000 83.000000
2.800000 56.000000
4.333000 89.000000
1.833000 46.000000
4.383000 82.000000
1.883000 51.000000
4.933000 86.000000
2.033000 53.000000
3.733000 79.000000
4.233000 81.000000
2.233000 60.000000
4.533000 82.000000
4.817000 77.000000
4.333000 76.000000
1.983000 59.000000
4.633000 80.000000
2.017000 49.000000
5.100000 96.000000
1.800000 53.000000
5.033000 77.000000
4.000000 77.000000
2.400000 65.000000
4.600000 81.000000
3.567000 71.000000
4.000000 70.000000
4.500000 81.000000
4.083000 93.000000
1.800000 53.000000
3.967000 89.000000
2.200000 45.000000
4.150000 86.000000
2.000000 58.000000
3.833000 78.000000
3.500000 66.000000
4.583000 76.000000
2.367000 63.000000
5.000000 88.000000
1.933000 52.000000
4.617000 93.000000
1.917000 49.000000
2.083000 57.000000
4.583000 77.000000
3.333000 68.000000
4.167000 81.000000
4.333000 81.000000
4.500000 73.000000
2.417000 50.000000
4.000000 85.000000
4.167000 74.000000
1.883000 55.000000
4.583000 77.000000
4.250000 83.000000
3.767000 83.000000
2.033000 51.000000
4.433000 78.000000
4.083000 84.000000
1.833000 46.000000
4.417000 83.000000
2.183000 55.000000
4.800000 81.000000
1.833000 57.000000
4.800000 76.000000
4.100000 84.000000
3.966000 77.000000
4.233000 81.000000
3.500000 87.000000
4.366000 77.000000
2.250000 51.000000
4.667000 78.000000
2.100000 60.000000
4.350000 82.000000
4.133000 91.000000
1.867000 53.000000
4.600000 78.000000
1.783000 46.000000
4.367000 77.000000
3.850000 84.000000
1.933000 49.000000
4.500000 83.000000
2.383000 71.000000
4.700000 80.000000
1.867000 49.000000
3.833000 75.000000
3.417000 64.000000
4.233000 76.000000
2.400000 53.000000
4.800000 94.000000
2.000000 55.000000
4.150000 76.000000
1.867000 50.000000
4.267000 82.000000
1.750000 54.000000
4.483000 75.000000
4.000000 78.000000
4.117000 79.000000
4.083000 78.000000
4.267000 78.000000
3.917000 70.000000
4.550000 79.000000
4.083000 70.000000
2.417000 54.000000
4.183000 86.000000
2.217000 50.000000
4.450000 90.000000
1.883000 54.000000
1.850000 54.000000
4.283000 77.000000
3.950000 79.000000
2.333000 64.000000
4.150000 75.000000
2.350000 47.000000
4.933000 86.000000
2.900000 63.000000
4.583000 85.000000
3.833000 82.000000
2.083000 57.000000
4.367000 82.000000
2.133000 67.000000
4.350000 74.000000
2.200000 54.000000
4.450000 83.000000
3.567000 73.000000
4.500000 73.000000
4.150000 88.000000
3.817000 80.000000
3.917000 71.000000
4.450000 83.000000
2.000000 56.000000
4.283000 79.000000
4.767000 78.000000
4.533000 84.000000
1.850000 58.000000
4.250000 83.000000
1.983000 43.000000
2.250000 60.000000
4.750000 75.000000
4.117000 81.000000
2.150000 46.000000
4.417000 90.000000
1.817000 46.000000
4.467000 74.000000
This diff is collapsed.
"Sepal Length","Sepal Width","Petal Length","Petal Width","Type"
5.1,3.5,1.4,0.2,"Iris-setosa"
4.9,3,1.4,0.2,"Iris-setosa"
4.7,3.2,1.3,0.2,"Iris-setosa"
4.6,3.1,1.5,0.2,"Iris-setosa"
5,3.6,1.4,0.2,"Iris-setosa"
5.4,3.9,1.7,0.4,"Iris-setosa"
4.6,3.4,1.4,0.3,"Iris-setosa"
5,3.4,1.5,0.2,"Iris-setosa"
4.4,2.9,1.4,0.2,"Iris-setosa"
4.9,3.1,1.5,0.1,"Iris-setosa"
5.4,3.7,1.5,0.2,"Iris-setosa"
4.8,3.4,1.6,0.2,"Iris-setosa"
4.8,3,1.4,0.1,"Iris-setosa"
4.3,3,1.1,0.1,"Iris-setosa"
5.8,4,1.2,0.2,"Iris-setosa"
5.7,4.4,1.5,0.4,"Iris-setosa"
5.4,3.9,1.3,0.4,"Iris-setosa"
5.1,3.5,1.4,0.3,"Iris-setosa"
5.7,3.8,1.7,0.3,"Iris-setosa"
5.1,3.8,1.5,0.3,"Iris-setosa"
5.4,3.4,1.7,0.2,"Iris-setosa"
5.1,3.7,1.5,0.4,"Iris-setosa"
4.6,3.6,1,0.2,"Iris-setosa"
5.1,3.3,1.7,0.5,"Iris-setosa"
4.8,3.4,1.9,0.2,"Iris-setosa"
5,3,1.6,0.2,"Iris-setosa"
5,3.4,1.6,0.4,"Iris-setosa"
5.2,3.5,1.5,0.2,"Iris-setosa"
5.2,3.4,1.4,0.2,"Iris-setosa"
4.7,3.2,1.6,0.2,"Iris-setosa"
4.8,3.1,1.6,0.2,"Iris-setosa"
5.4,3.4,1.5,0.4,"Iris-setosa"
5.2,4.1,1.5,0.1,"Iris-setosa"
5.5,4.2,1.4,0.2,"Iris-setosa"
4.9,3.1,1.5,0.1,"Iris-setosa"
5,3.2,1.2,0.2,"Iris-setosa"
5.5,3.5,1.3,0.2,"Iris-setosa"
4.9,3.1,1.5,0.1,"Iris-setosa"
4.4,3,1.3,0.2,"Iris-setosa"
5.1,3.4,1.5,0.2,"Iris-setosa"
5,3.5,1.3,0.3,"Iris-setosa"
4.5,2.3,1.3,0.3,"Iris-setosa"
4.4,3.2,1.3,0.2,"Iris-setosa"
5,3.5,1.6,0.6,"Iris-setosa"
5.1,3.8,1.9,0.4,"Iris-setosa"
4.8,3,1.4,0.3,"Iris-setosa"
5.1,3.8,1.6,0.2,"Iris-setosa"
4.6,3.2,1.4,0.2,"Iris-setosa"
5.3,3.7,1.5,0.2,"Iris-setosa"
5,3.3,1.4,0.2,"Iris-setosa"
7,3.2,4.7,1.4,"Iris-versicolor"
6.4,3.2,4.5,1.5,"Iris-versicolor"
6.9,3.1,4.9,1.5,"Iris-versicolor"
5.5,2.3,4,1.3,"Iris-versicolor"
6.5,2.8,4.6,1.5,"Iris-versicolor"
5.7,2.8,4.5,1.3,"Iris-versicolor"
6.3,3.3,4.7,1.6,"Iris-versicolor"
4.9,2.4,3.3,1,"Iris-versicolor"
6.6,2.9,4.6,1.3,"Iris-versicolor"
5.2,2.7,3.9,1.4,"Iris-versicolor"
5,2,3.5,1,"Iris-versicolor"
5.9,3,4.2,1.5,"Iris-versicolor"
6,2.2,4,1,"Iris-versicolor"
6.1,2.9,4.7,1.4,"Iris-versicolor"
5.6,2.9,3.6,1.3,"Iris-versicolor"
6.7,3.1,4.4,1.4,"Iris-versicolor"
5.6,3,4.5,1.5,"Iris-versicolor"
5.8,2.7,4.1,1,"Iris-versicolor"
6.2,2.2,4.5,1.5,"Iris-versicolor"
5.6,2.5,3.9,1.1,"Iris-versicolor"
5.9,3.2,4.8,1.8,"Iris-versicolor"
6.1,2.8,4,1.3,"Iris-versicolor"
6.3,2.5,4.9,1.5,"Iris-versicolor"
6.1,2.8,4.7,1.2,"Iris-versicolor"
6.4,2.9,4.3,1.3,"Iris-versicolor"
6.6,3,4.4,1.4,"Iris-versicolor"
6.8,2.8,4.8,1.4,"Iris-versicolor"
6.7,3,5,1.7,"Iris-versicolor"
6,2.9,4.5,1.5,"Iris-versicolor"
5.7,2.6,3.5,1,"Iris-versicolor"
5.5,2.4,3.8,1.1,"Iris-versicolor"
5.5,2.4,3.7,1,"Iris-versicolor"
5.8,2.7,3.9,1.2,"Iris-versicolor"
6,2.7,5.1,1.6,"Iris-versicolor"
5.4,3,4.5,1.5,"Iris-versicolor"
6,3.4,4.5,1.6,"Iris-versicolor"
6.7,3.1,4.7,1.5,"Iris-versicolor"
6.3,2.3,4.4,1.3,"Iris-versicolor"
5.6,3,4.1,1.3,"Iris-versicolor"
5.5,2.5,4,1.3,"Iris-versicolor"
5.5,2.6,4.4,1.2,"Iris-versicolor"
6.1,3,4.6,1.4,"Iris-versicolor"
5.8,2.6,4,1.2,"Iris-versicolor"
5,2.3,3.3,1,"Iris-versicolor"
5.6,2.7,4.2,1.3,"Iris-versicolor"
5.7,3,4.2,1.2,"Iris-versicolor"
5.7,2.9,4.2,1.3,"Iris-versicolor"
6.2,2.9,4.3,1.3,"Iris-versicolor"
5.1,2.5,3,1.1,"Iris-versicolor"
5.7,2.8,4.1,1.3,"Iris-versicolor"
6.3,3.3,6,2.5,"Iris-virginica"
5.8,2.7,5.1,1.9,"Iris-virginica"
7.1,3,5.9,2.1,"Iris-virginica"
6.3,2.9,5.6,1.8,"Iris-virginica"
6.5,3,5.8,2.2,"Iris-virginica"
7.6,3,6.6,2.1,"Iris-virginica"
4.9,2.5,4.5,1.7,"Iris-virginica"
7.3,2.9,6.3,1.8,"Iris-virginica"
6.7,2.5,5.8,1.8,"Iris-virginica"
7.2,3.6,6.1,2.5,"Iris-virginica"
6.5,3.2,5.1,2,"Iris-virginica"
6.4,2.7,5.3,1.9,"Iris-virginica"
6.8,3,5.5,2.1,"Iris-virginica"
5.7,2.5,5,2,"Iris-virginica"
5.8,2.8,5.1,2.4,"Iris-virginica"
6.4,3.2,5.3,2.3,"Iris-virginica"
6.5,3,5.5,1.8,"Iris-virginica"
7.7,3.8,6.7,2.2,"Iris-virginica"
7.7,2.6,6.9,2.3,"Iris-virginica"
6,2.2,5,1.5,"Iris-virginica"
6.9,3.2,5.7,2.3,"Iris-virginica"
5.6,2.8,4.9,2,"Iris-virginica"
7.7,2.8,6.7,2,"Iris-virginica"
6.3,2.7,4.9,1.8,"Iris-virginica"
6.7,3.3,5.7,2.1,"Iris-virginica"
7.2,3.2,6,1.8,"Iris-virginica"
6.2,2.8,4.8,1.8,"Iris-virginica"
6.1,3,4.9,1.8,"Iris-virginica"
6.4,2.8,5.6,2.1,"Iris-virginica"
7.2,3,5.8,1.6,"Iris-virginica"
7.4,2.8,6.1,1.9,"Iris-virginica"
7.9,3.8,6.4,2,"Iris-virginica"
6.4,2.8,5.6,2.2,"Iris-virginica"
6.3,2.8,5.1,1.5,"Iris-virginica"
6.1,2.6,5.6,1.4,"Iris-virginica"
7.7,3,6.1,2.3,"Iris-virginica"
6.3,3.4,5.6,2.4,"Iris-virginica"
6.4,3.1,5.5,1.8,"Iris-virginica"
6,3,4.8,1.8,"Iris-virginica"
6.9,3.1,5.4,2.1,"Iris-virginica"
6.7,3.1,5.6,2.4,"Iris-virginica"
6.9,3.1,5.1,2.3,"Iris-virginica"
5.8,2.7,5.1,1.9,"Iris-virginica"
6.8,3.2,5.9,2.3,"Iris-virginica"
6.7,3.3,5.7,2.5,"Iris-virginica"
6.7,3,5.2,2.3,"Iris-virginica"
6.3,2.5,5,1.9,"Iris-virginica"
6.5,3,5.2,2,"Iris-virginica"
6.2,3.4,5.4,2.3,"Iris-virginica"
5.9,3,5.1,1.8,"Iris-virginica"
File added
File added
This diff is collapsed.
Bread,Soda,Milk
Beer,Bread
Beer,Soda,Diaper,Milk
Beer,Bread,Diaper,Milk
Soda,Diaper,Milk
***************************************************************************
***************************************************************************
*** messy_data ***
***************************************************************************
***************************************************************************
This dataset is an adaption of an existing dataset to highlight some common
issues (or variants of them) that one might face across various datasets.
This is not real data, but is based on values from the Auto-Mpg Data.
The original data was obtained from:
https://archive.ics.uci.edu/ml/datasets/auto+mpg
but was modified to include some formatting issues as well as removing some
values.
Missing values in the original dataset were sometimes denoted
with a question mark. Some missing values were introduced, too.
Specifically zeroes in the attributes mpg and displacement can be
considered missing values.
For reference, the description of the original dataset is provided below.
***************************************************************************
***************************************************************************
*** Original dataset description ***
***************************************************************************
***************************************************************************
1. Title: Auto-Mpg Data
2. Sources:
(a) Origin: This dataset was taken from the StatLib library which is
maintained at Carnegie Mellon University. The dataset was
used in the 1983 American Statistical Association Exposition.
(c) Date: July 7, 1993
3. Past Usage:
- See 2b (above)
- Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning.
In Proceedings on the Tenth International Conference of Machine
Learning, 236-243, University of Massachusetts, Amherst. Morgan
Kaufmann.
4. Relevant Information:
This dataset is a slightly modified version of the dataset provided in
the StatLib library. In line with the use by Ross Quinlan (1993) in
predicting the attribute "mpg", 8 of the original instances were removed
because they had unknown values for the "mpg" attribute. The original
dataset is available in the file "auto-mpg.data-original".
"The data concerns city-cycle fuel consumption in miles per gallon,
to be predicted in terms of 3 multivalued discrete and 5 continuous
attributes." (Quinlan, 1993)
5. Number of Instances: 398
6. Number of Attributes: 9 including the class attribute
7. Attribute Information:
1. mpg: continuous
2. cylinders: multi-valued discrete
3. displacement: continuous
4. horsepower: continuous
5. weight: continuous
6. acceleration: continuous
7. model year: multi-valued discrete
8. origin: multi-valued discrete
9. car name: string (unique for each instance)
8. Missing Attribute Values: horsepower has 6 missing values
messy_data
mpg cylinders displacement horsepower weight acceleration modelyear origin carname
mpg cyl disp hp w acc yr org name
18 8 ? 130 3'504 12.0 70 1 chevrolet chevelle malibu
15 8 350 165 3'693 11,5 70 1 buick skylark 320
18 8 ? 150 3'436 11.0 70 1 plymouth satellite
16 8 ? 150 3'433 12.0 70 1 amc rebel sst
17 8 0 140 3'449 10,5 70 1 ford torino
15 8 429 198 4'341 10.0 70 1 ford galaxie 500
14 8 454 220 4'354 9.0 70 1 chevrolet impala
14 8 ? 215 4312 8,5 70 1 plymouth fury iii
14 8 455 225 4425 10.0 70 1 pontiac catalina
15 8 390 190 3'850 8,5 70 1 amc ambassador dpl
15 8 0 170 3'563 10.0 70 1 dodge challenger se
14 8 ? 160 3'609 8.0 70 1 plymouth 'cuda 340
99 8 ? 150 3'761 9,5 70 1 chevrolet monte carlo
14 8 ? 225 3'086 10.0 70 1 buick estate wagon (sw)
24 4 113 95 2'372 15.0 70 3 toyota corona mark ii
22 6 95 2'833 15,5 70 1 plymouth duster
0 6 199 97 2'774 15,5 70 1 amc hornet
21 6 ? 85 2'587 16.0 70 1 ford maverick
27 4 97 88 2'130 14,5 70 3 datsun pl510
26 4 46 1'835 20,5 70 2 volkswagen 1131 deluxe sedan
33 4 105 74 2190 14.2 81 2 volkswagen jetta
33.7 4 107 75 2210 14.4 81 3 honda prelude
32.4 4 108 75 2350 16.8 81 3 toyota corolla
32.9 4 119 100 2615 14.8 81 3 datsun 200sx
31.6 4 120 74 2635 18.3 81 3 mazda 626
28.1 4 141 80 3'230 20.4 81 2 peugeot 505s turbo diesel
30.7 6 145 76 3'160 19.6 81 2 volvo diesel
0 6 168 116 2'900 12.6 81 3 toyota cressida
24.2 6 146 120 2'930 13.8 81 3 datsun 810 maxima
File added
You may use the lists of names for any purpose, so long as credit is given
in any published work. You may also redistribute the list if you
provide the recipients with a copy of this README file. The lists are
not in the public domain (I retain the copyright on the lists) but are
freely redistributable.
If you have any additions to the lists of names, I would appreciate
receiving them.
My email address is mkant+@cs.cmu.edu.
Mark Kantrowitz
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\ No newline at end of file
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