upgrade minimum sklearn

.github/workflows/build.yml

@@ -7,7 +7,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.9', '3.10', '3.11', '3.12']
     runs-on: ${{ matrix.os }}
 
     steps:

.github/workflows/publish.yml

@@ -21,9 +21,9 @@ jobs:
       - name: Build wheels
         uses: pypa/[email protected]
         env:
-          CIBW_BUILD: cp38-* cp39-* cp310-* cp311-* cp312-*
+          CIBW_BUILD: cp39-* cp310-* cp311-* cp312-*
           CIBW_SKIP: pp* *i686* *win32 *musllinux*
-          CIBW_PROJECT_REQUIRES_PYTHON: '>=3.8,<3.13'
+          CIBW_PROJECT_REQUIRES_PYTHON: '>=3.9,<3.13'
           CIBW_BEFORE_BUILD: pip install --verbose --editable .
           CIBW_ARCHS_LINUX: auto64
           CIBW_ARCHS_MACOS: x86_64 universal2 arm64

docs/getting_started/installation.rst

@@ -8,9 +8,9 @@ Prerequisites
 
 The quantile-forest package requires the following dependencies:
 
-* python (>=3.8)
+* python (>=3.9)
 * numpy (>=1.23)
-* scikit-learn (>=1.0)
+* scikit-learn (>=1.5)
 * scipy (>=1.4)
 
 Installation

pyproject.toml

@@ -6,13 +6,13 @@ requires = [
     "Cython>=3.0a4",
     "numpy>=1.23",
     "scipy>=1.4",
-    "scikit-learn>=1.0",
+    "scikit-learn>=1.5",
 ]
 
 [tool.black]
 line-length = 99
 preview = true
-target_version = ["py38", "py39", "py310", "py311", "py312"]
+target_version = ["py39", "py310", "py311", "py312"]
 
 [tool.cython-lint]
 ignore = ["E741"]

quantile_forest/_min_dependencies.py

@@ -6,7 +6,7 @@
 CYTHON_MIN_VERSION = "3.0a4"
 NUMPY_MIN_VERSION = "1.23"
 SCIPY_MIN_VERSION = "1.4"
-SKLEARN_MIN_VERSION = "1.0"
+SKLEARN_MIN_VERSION = "1.5"
 
 # 'build' and 'install' is included to have structured metadata for CI.
 # The values are (version_spec, comma separated tags).

quantile_forest/_quantile_forest.py

@@ -94,9 +94,7 @@ def __init__(
     ):
         """Initialize base quantile forest regressor."""
         init_dict = {
-            (
-                "base_estimator" if sklearn_version < parse_version("1.2.0") else "estimator"
-            ): estimator,
+            "estimator": estimator,
             "n_estimators": n_estimators,
             "estimator_params": estimator_params,
             "bootstrap": bootstrap,
@@ -1347,6 +1345,7 @@ def __init__(
                 "min_impurity_decrease",
                 "random_state",
                 "ccp_alpha",
+                "monotonic_cst",
             ),
             "bootstrap": bootstrap,
             "oob_score": oob_score,
@@ -1357,8 +1356,6 @@ def __init__(
             "max_samples": max_samples,
             "max_samples_leaf": max_samples_leaf,
         }
-        if sklearn_version >= parse_version("1.4.0"):
-            init_dict["estimator_params"] += ("monotonic_cst",)
         super(RandomForestQuantileRegressor, self).__init__(**init_dict)
 
         self.default_quantiles = default_quantiles
@@ -1680,6 +1677,7 @@ def __init__(
                 "min_impurity_decrease",
                 "random_state",
                 "ccp_alpha",
+                "monotonic_cst",
             ),
             "bootstrap": bootstrap,
             "oob_score": oob_score,
@@ -1690,8 +1688,6 @@ def __init__(
             "max_samples": max_samples,
             "max_samples_leaf": max_samples_leaf,
         }
-        if sklearn_version >= parse_version("1.4.0"):
-            init_dict["estimator_params"] += ("monotonic_cst",)
         super(ExtraTreesQuantileRegressor, self).__init__(**init_dict)
 
         self.default_quantiles = default_quantiles

setup.py

@@ -52,7 +52,6 @@ def write_version_py():
     "Operating System :: POSIX",
     "Operating System :: Unix",
     "Operating System :: MacOS",
-    "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",