# scikit-learn__scikit-learn-13496
# Loki Mode Multi-Agent Patch
# Attempts: 1

This is a scikit-learn repository issue but the current working directory doesn't contain the scikit-learn codebase. Based on the issue description and architect's analysis, I can generate the patch for the scikit-learn repository. Let me create the patch based on the standard scikit-learn file structure:

```
--- a/sklearn/ensemble/iforest.py
+++ b/sklearn/ensemble/iforest.py
@@ -120,6 +120,12 @@ class IsolationForest(BaseBagging, OutlierMixin):
         verbose : int, optional (default=0)
             Controls the verbosity of the tree building process.
 
+        warm_start : bool, optional (default=False)
+            When set to ``True``, reuse the solution of the previous call to fit
+            and add more estimators to the ensemble, otherwise, just fit a whole
+            new forest. See :term:`the Glossary <warm_start>`.
+
+
         Attributes
         ----------
         estimators_ : list of DecisionTreeClassifier
@@ -173,7 +179,8 @@ class IsolationForest(BaseBagging, OutlierMixin):
                  n_jobs=None,
                  behaviour='old',
                  random_state=None,
-                 verbose=0):
+                 verbose=0,
+                 warm_start=False):
         super().__init__(
             base_estimator=ExtraTreeRegressor(
                 max_features=1,
@@ -185,6 +192,7 @@ class IsolationForest(BaseBagging, OutlierMixin):
             n_estimators=n_estimators,
             max_samples=max_samples,
             max_features=max_features,
+            warm_start=warm_start,
             n_jobs=n_jobs,
             random_state=random_state,
             verbose=verbose)
--- a/sklearn/ensemble/tests/test_iforest.py
+++ b/sklearn/ensemble/tests/test_iforest.py
@@ -295,3 +295,18 @@ def test_iforest_chunks_works2(
     ):
         with pytest.raises(Warning, match='y'):
             check_warning_when_y_not_none(IsolationForest())
+
+
+def test_iforest_warm_start():
+    """Test that warm_start works correctly."""
+    X = iris.data
+    # Test warm_start with n_estimators
+    clf = IsolationForest(n_estimators=5, warm_start=True, random_state=0)
+    clf.fit(X)
+    assert len(clf.estimators_) == 5
+
+    # Fit with more estimators
+    clf.n_estimators = 10
+    clf.fit(X)
+    assert len(clf.estimators_) == 10
+    assert_true(hasattr(clf, "estimators_"))
```