Quick start at Machine Learning with Scikit-Learn

This is the first class topic of Machine Learning at TPAA6 discipline at IFSP-CJO.

 

Simple example of Machine Learning with DecisionTreeClassifier of scikit-learn library using Iris Dataset.

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Scatter Plot with Matlablib

Decision Tree Result

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Build With

• Matlab
• Jupyter Lab
  • Python3

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Instalation

$ pip install -U matplotlib
$ pip install -U scikit-learn

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Usage

To use <project_name>, follow these steps:

Step 1

• Open the iris-scikitlearn.ipynb file on Jupyter Lab and run it.

Step 2

• Execute the model analysis script to get the performance of Decision Tree

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Contributing

1. Fork this repository.
2. Create a branch: $ git checkout -b <branch_name>
3. Make your changes and commit them: $ git commit -m '<commit_message>'
4. Push to the original branch: $ git push origin <project_name>/<location>
5. Create the pull request of the fork branch to our master.

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References

Based on Flavio Souza class check his disciplines at web profile.

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Contributors

Lucas Ventura 💻 📖