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iris Dataset classification (pre-processing, Scaling, and plotting ) // AdaBoost and Random forest

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Iris Classification - AdaBoost and Random Forest

using Sklearn.ensemble for Adaboost and Random Forest for this project's classifiers. first of all import the dataset and select 2 Best features and then after scaling, plot them with scatter plot using matplotlib. then train two classifier and compare them for findout wich one is better for this dataset with two features. then check the scores and finally plot them after classification to virtualize the result.

  • adaboost

Iris , AdaBoost

  • random forest

Iris , RandomForest

Libraries in use:

Sklearn

Pandas

Numpy

Matplotlib

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