Is is possible to see the input labels for a randomforest model?

Question

I have a random forest model built like this:
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
model = RandomForestClassifier(random_state=0)

X_train,X_test,y_train,y_test = train_test_split(X, y, test_size = 0.2, random_state=42, stratify=y)

model.fit(X_train, y_train)

Is there any method I can call (or attribute I can use) to see the column names used to make the  model?
Thanks

cmn · Answer

It is impossible to retrieve column names from a trained Random forest classifier from my experience, there is also a previous answer for an identical question.

10xAI · Answer

You can get all the Trees using
clf.estimators_
Then you can traverse the Tree using custom code.[Check here]
 Then you can take it to whatever format you want i.e. Array/DataFrame
A sample code to view one of the Tree
from sklearn import datasets
iris = datasets.load_iris()
X = iris.data  
y = iris.target

clf = RandomForestClassifier(max_depth=3, random_state=0)
clf.fit(X, y)

model  = clf.estimators_[0]  # Checking the first Tree

from sklearn.tree import export_text
tree_rules = export_text(model, feature_names=iris.feature_names)
print(tree_rules)

Is is possible to see the input labels for a randomforest model?

2 Answers

A sample code to view one of the Tree

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