UBISS2024exam: Difference between revisions

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from sklearn.model_selection import train_test_split
from everywhereml.sklearn.ensemble import RandomForestClassifier


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X = df[["X", "Y", "Z"]].diff().iloc[1:].values
max_leaf_nodes = 30
 
 
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clf = RandomForestClassifier(n_estimators=100, max_leaf_nodes=max_leaf_nodes)


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y = df.Label.iloc[1:].values
clf.fit(X_train, y_train)


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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)
print(f'Score: {clf.score(X_test, y_test):3.3f}')
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Revision as of 13:40, 13 June 2024

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from everywhereml.sklearn.ensemble import RandomForestClassifier

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max_leaf_nodes = 30


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clf = RandomForestClassifier(n_estimators=100, max_leaf_nodes=max_leaf_nodes)

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clf.fit(X_train, y_train)

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print(f'Score: {clf.score(X_test, y_test):3.3f}')
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