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Create README.txt
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macrel/data/models/README.txt

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Load data
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Train RF with OOB estimators
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Train RF without OOB estimators
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Fitting models
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Save AMP model
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Predict test
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# AMP (unbalanced training) CLASSIFIER
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Accuracy: 0.926
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MCC: 0.862
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Confusion matrix:
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[[784 136]
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[ 0 920]]
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precision recall f1-score support
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AMP 1.000 0.852 0.920 920
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NAMP 0.871 1.000 0.931 920
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accuracy 0.926 1840
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macro avg 0.936 0.926 0.926 1840
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weighted avg 0.936 0.926 0.926 1840
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Load bench set
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Train bench set
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Test bench set
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# AMP (benchmark training) CLASSIFIER
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Accuracy: 0.946
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MCC: 0.893
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Confusion matrix:
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[[846 74]
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[ 26 894]]
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precision recall f1-score support
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AMP 0.970 0.920 0.944 920
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NAMP 0.924 0.972 0.947 920
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accuracy 0.946 1840
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macro avg 0.947 0.946 0.946 1840
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weighted avg 0.947 0.946 0.946 1840
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Load datasets
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Fit Hemo sets
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Save Hemo model
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# Hemo CLASSIFIER
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Accuracy: 0.936
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MCC: 0.873
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Confusion matrix:
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[[102 8]
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[ 6 104]]
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precision recall f1-score support
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Hemo 0.944 0.927 0.936 110
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NonHemo 0.929 0.945 0.937 110
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accuracy 0.936 220
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macro avg 0.937 0.936 0.936 220
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weighted avg 0.937 0.936 0.936 220
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January 30th 2023
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scikit-learn 1.1.2

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