This notebook includes coding and notes for predicting iris flower species using random forest classification machine learning in python.
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Successfully trained, tested and deployed iris flower species machine learning model in python using the random forest classifier algorithm.
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Achieved accuracy score of 0.9737 and f1 score of 0.9717 indicating the model worked well.
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Fine tuned model using various tree lengths.
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Visualized results with confusion matrix heatmap and standard plots.
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Deployed the model on fictional flower data.