https://github.com/isaqueiros/iris-predictions-knnclassifier_and_decisiontree

This notebook demonstrates the basic application of two common machine learning algorithms, KNN and Decision Tree, for species classification using the classic Iris dataset. This is a beginner-friendly guide for understanding and applying basic classification techniques in Python using scikit-learn.
https://github.com/isaqueiros/iris-predictions-knnclassifier_and_decisiontree

decision-tree-classifier knn-classifier sklearn

Last synced: 2 months ago
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This notebook demonstrates the basic application of two common machine learning algorithms, KNN and Decision Tree, for species classification using the classic Iris dataset. This is a beginner-friendly guide for understanding and applying basic classification techniques in Python using scikit-learn.

• Host: GitHub
• URL: https://github.com/isaqueiros/iris-predictions-knnclassifier_and_decisiontree
• Owner: isaqueiros
• Created: 2024-11-19T12:18:18.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-19T12:44:10.000Z (over 1 year ago)
• Last Synced: 2025-03-17T04:48:25.627Z (over 1 year ago)
• Topics: decision-tree-classifier, knn-classifier, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 105 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Iris-predictions-KNNClassifier_and_DecisionTree

This notebook demonstrates the basic application of two common machine learning algorithms for species classification using the classic Iris dataset. The models used are:

- K-Nearest Neighbors (KNN)

- Decision Tree Classifier

This is a beginner-friendly guide for understanding and applying basic classification techniques in Python using scikit-learn.

The model is applied to dataset Iris, which is supplied separately in .csv format.