diff --git a/pyproject.toml b/pyproject.toml
index 1284e7c..a451e21 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -32,6 +32,7 @@ classifiers = [
 requires-python = ">=3.8,<3.14"
 dependencies = [
     "scikit-learn>=1.2.2",
+    "typing-extensions>=4.1.0; python_full_version < '3.11'"
 ]
 
 [dependency-groups]
diff --git a/requirements.txt b/requirements.txt
index 1fb8114..b52fd23 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1 +1,2 @@
 scikit-learn>=1.2.2
+typing-extensions>=4.1.0; python_version < "3.11"
\ No newline at end of file
diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py
index 1f233cf..b99dd74 100644
--- a/src/linearboost/linear_boost.py
+++ b/src/linearboost/linear_boost.py
@@ -1,7 +1,14 @@
 from __future__ import annotations
 
+import sys
+import warnings
 from numbers import Integral, Real
 
+if sys.version_info >= (3, 11):
+    from typing import Self
+else:
+    from typing_extensions import Self
+
 import numpy as np
 from sklearn.base import clone
 from sklearn.ensemble import AdaBoostClassifier
@@ -65,13 +72,18 @@ class LinearBoostClassifier(AdaBoostClassifier):
 
     algorithm : {'SAMME', 'SAMME.R'}, default='SAMME'
         If 'SAMME' then use the SAMME discrete boosting algorithm.
-        If 'SAMME.R' then use the SAMME.R real boosting algorithm.
+        If 'SAMME.R' then use the SAMME.R real boosting algorithm
+        (only available in scikit-learn < 1.6).
         The SAMME.R algorithm typically converges faster than SAMME,
         achieving a lower test error with fewer boosting iterations.
 
-        .. deprecated:: sklearn 1.6
-            `algorithm` is deprecated and will be removed in sklearn 1.8. This
-            estimator only implements the 'SAMME' algorithm.
+        .. deprecated:: scikit-learn 1.4
+            `"SAMME.R"` is deprecated and will be removed in scikit-learn 1.6.
+            '"SAMME"' will become the default.
+
+        .. deprecated:: scikit-learn 1.6
+            `algorithm` is deprecated and will be removed in scikit-learn 1.8.
+            This estimator only implements the 'SAMME' algorithm in scikit-learn >= 1.6.
 
     scaler : str, default='minmax'
         Specifies the scaler to apply to the data. Options include:
@@ -111,21 +123,21 @@ class LinearBoostClassifier(AdaBoostClassifier):
         where:
         - y_true: Ground truth (correct) target values.
         - y_pred: Estimated target values.
-        - sample_weight: Sample weights.
+        - sample_weight: Sample weights (optional).
 
     Attributes
     ----------
     estimator_ : estimator
         The base estimator (SEFR) from which the ensemble is grown.
 
-        .. versionadded:: sklearn 1.2
+        .. versionadded:: scikit-learn 1.2
            `base_estimator_` was renamed to `estimator_`.
 
     base_estimator_ : estimator
         The base estimator from which the ensemble is grown.
 
-        .. deprecated:: sklearn 1.2
-            `base_estimator_` is deprecated and will be removed in sklearn 1.4.
+        .. deprecated:: scikit-learn 1.2
+            `base_estimator_` is deprecated and will be removed in scikit-learn 1.4.
             Use `estimator_` instead.
 
     estimators_ : list of classifiers
@@ -176,10 +188,9 @@ class LinearBoostClassifier(AdaBoostClassifier):
     _parameter_constraints: dict = {
         "n_estimators": [Interval(Integral, 1, None, closed="left")],
         "learning_rate": [Interval(Real, 0, None, closed="neither")],
-        "algorithm": [
-            StrOptions({"SAMME", "SAMME.R"}),
-            Hidden(StrOptions({"deprecated"})),
-        ],
+        "algorithm": [StrOptions({"SAMME"}), Hidden(StrOptions({"deprecated"}))]
+        if SKLEARN_V1_6_OR_LATER
+        else [StrOptions({"SAMME", "SAMME.R"})],
         "scaler": [StrOptions({s for s in _scalers})],
         "class_weight": [
             StrOptions({"balanced_subsample", "balanced"}),
@@ -257,7 +268,7 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]:
 
         return X, y
 
-    def fit(self, X, y, sample_weight=None) -> "LinearBoostClassifier":
+    def fit(self, X, y, sample_weight=None) -> Self:
         X, y = self._check_X_y(X, y)
         self.classes_ = np.unique(y)
         self.n_classes_ = self.classes_.shape[0]
@@ -291,7 +302,14 @@ def fit(self, X, y, sample_weight=None) -> "LinearBoostClassifier":
             else:
                 sample_weight = expanded_class_weight
 
-        return super().fit(X_transformed, y, sample_weight)
+        with warnings.catch_warnings():
+            if SKLEARN_V1_6_OR_LATER:
+                warnings.filterwarnings(
+                    "ignore",
+                    category=FutureWarning,
+                    message=".*parameter 'algorithm' is deprecated.*",
+                )
+            return super().fit(X_transformed, y, sample_weight)
 
     def _boost(self, iboost, X, y, sample_weight, random_state):
         estimator = self._make_estimator(random_state=random_state)
diff --git a/src/linearboost/sefr.py b/src/linearboost/sefr.py
index 29915ff..db6477f 100644
--- a/src/linearboost/sefr.py
+++ b/src/linearboost/sefr.py
@@ -1,5 +1,12 @@
 from __future__ import annotations
 
+import sys
+
+if sys.version_info >= (3, 11):
+    from typing import Self
+else:
+    from typing_extensions import Self
+
 import numpy as np
 from sklearn.base import BaseEstimator
 from sklearn.linear_model._base import LinearClassifierMixin
@@ -139,7 +146,7 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]:
         return X, y
 
     @_fit_context(prefer_skip_nested_validation=True)
-    def fit(self, X, y, sample_weight=None) -> "SEFR":
+    def fit(self, X, y, sample_weight=None) -> Self:
         """
         Fit the model according to the given training data.
 
diff --git a/uv.lock b/uv.lock
index d7c393a..095ddbb 100644
--- a/uv.lock
+++ b/uv.lock
@@ -74,6 +74,7 @@ source = { editable = "." }
 dependencies = [
     { name = "scikit-learn", version = "1.3.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.9'" },
     { name = "scikit-learn", version = "1.6.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.9'" },
+    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
 
 [package.dev-dependencies]
@@ -85,7 +86,10 @@ dev = [
 ]
 
 [package.metadata]
-requires-dist = [{ name = "scikit-learn", specifier = ">=1.2.2" }]
+requires-dist = [
+    { name = "scikit-learn", specifier = ">=1.2.2" },
+    { name = "typing-extensions", marker = "python_full_version < '3.11'", specifier = ">=4.1.0" },
+]
 
 [package.metadata.requires-dev]
 dev = [
@@ -575,3 +579,12 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c7/32/b0963458706accd9afcfeb867c0f9175a741bf7b19cd424230714d722198/tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69", size = 109383 },
     { url = "https://files.pythonhosted.org/packages/6e/c2/61d3e0f47e2b74ef40a68b9e6ad5984f6241a942f7cd3bbfbdbd03861ea9/tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc", size = 14257 },
 ]
+
+[[package]]
+name = "typing-extensions"
+version = "4.13.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/0e/3e/b00a62db91a83fff600de219b6ea9908e6918664899a2d85db222f4fbf19/typing_extensions-4.13.0.tar.gz", hash = "sha256:0a4ac55a5820789d87e297727d229866c9650f6521b64206413c4fbada24d95b", size = 106520 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e0/86/39b65d676ec5732de17b7e3c476e45bb80ec64eb50737a8dce1a4178aba1/typing_extensions-4.13.0-py3-none-any.whl", hash = "sha256:c8dd92cc0d6425a97c18fbb9d1954e5ff92c1ca881a309c45f06ebc0b79058e5", size = 45683 },
+]