X=df.drop('class', axis=1)
y=df['class']
X=pd.get_dummies(X, drop_first='True')
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=101)
from sklearn.ensemble import AdaBoostClassifier
model=AdaBoostClassifier(n_estimators=1)
model.fit(X_train, y_train)
prediction = model.predict(X_test)
from sklearn.metrics import accuracy_score, classification_report,
plot_confusion_matrix
print(classification_report(y_test, prediction))
''' im learning AdaBoostclassification, where i got output 1 in each and every columns here i have attach the screenshot as well
why im getting 1 in precision, recall, F1-score, accuracy, macro avg & weighted avg all shows value 1, so whats the mistake here
i was trying to know the classification report and know im confuse what it means
