https://github.com/abhinav-codealchemist/flower-species-recognition-using-ml

Recognition of Flower Species Using Decision Trees & Random Forest Classifier
https://github.com/abhinav-codealchemist/flower-species-recognition-using-ml

decision-tree flower-species jupyter-notebook machine-learning python random-forest-classifier recognition

Last synced: 3 months ago
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Recognition of Flower Species Using Decision Trees & Random Forest Classifier

• Host: GitHub
• URL: https://github.com/abhinav-codealchemist/flower-species-recognition-using-ml
• Owner: abhinav-codealchemist
• Created: 2019-01-11T09:45:34.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-03-03T15:08:20.000Z (about 6 years ago)
• Last Synced: 2025-01-13T09:34:49.205Z (4 months ago)
• Topics: decision-tree, flower-species, jupyter-notebook, machine-learning, python, random-forest-classifier, recognition
• Language: Jupyter Notebook
• Size: 481 KB
• Stars: 2
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Flower-Species-Recognition-Using-ML

Recognition of Flower Species Using Decision Trees & Random Forest Classifier

This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other. 

https://archive.ics.uci.edu/ml/datasets/iris

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