Can an output class be defaulted?
I don't think there is a standard method to do this. But if you use a probabilistic model you can use the predicted probability together with thresholds on each class to only allow classifications that you deem certain enough. Then if the class with the highest probability does not meet the threshold you can set it to the default class.

I tested it out with sklearn and numpy, this could be an approach:

# Train probabilistic classifier
clf.fit(X_train, y_train)

# Get probabilities
probas = clf.predict_proba(X_test)

# Get the class with highest probability
highest_proba_class = np.argmax(probas, axis=1)

# Set different thresholds per class
thresholds = np.array([0.9, 0.2, 0.5])

# Init our prediction array
predictions = np.zeros_like(highest_proba_class)

# Set a default class to set if we don't reach threshold
default_class = 2

# Loop over predictions
for idx, highest_class in enumerate(highest_proba_class):

    # Threshold check if threshold was met, otherwise set default
    if probas[idx][highest_class] &gt;= thresholds[highest_class]:
        predictions[idx] = highest_class
    else:
        predictions[idx] = default_class