Confusion Matrix Report#

Imports#

import pandas as pd
from sklearn.datasets import load_iris
from sklearn.ensemble import AdaBoostClassifier
from sklearn.model_selection import train_test_split

from deepchecks.tabular import Dataset
from deepchecks.tabular.checks.performance import ConfusionMatrixReport

Generating data#

iris = load_iris(as_frame=True)
clf = AdaBoostClassifier()
frame = iris.frame
X = iris.data
y = iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
clf.fit(X_train, y_train)
ds = Dataset(pd.concat([X_test, y_test], axis=1),
            features=iris.feature_names,
            label='target')

Running confusion_matrix_report check#

check = ConfusionMatrixReport()
check.run(ds, clf)

Confusion Matrix Report

Calculate the confusion matrix of the model on the given dataset.

Additional Outputs


Total running time of the script: ( 0 minutes 0.094 seconds)

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