update sklearn dependency

doc/examples/py_double_ml_apo.ipynb

@@ -45,7 +45,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "At first, let us generate data according to the [make_irm_data_discrete_treatments](https://docs.doubleml.org/dev/api/generated/doubleml.datasets.make_irm_data_discrete_treatments.html#doubleml.datasets.make_irm_data_discrete_treatments) data generating process. The process generates data with a continuous\n",
+    "At first, let us generate data according to the [make_irm_data_discrete_treatments](https://docs.doubleml.org/dev/api/generated/doubleml.irm.datasets.make_irm_data_discrete_treatments.html#doubleml.irm.datasets.make_irm_data_discrete_treatments) data generating process. The process generates data with a continuous\n",
     "treatment variable and contains the true individual treatment effects (ITEs) with respect to option of not getting treated.\n",
     "\n",
     "According to the continuous treatment variable, the treatment is discretized into multiple levels, based on quantiles. Using the *oracle* ITEs, enables the comparison to the true APOs and averate treatment effects (ATEs) for the different levels of the treatment variable.\n",
@@ -518,7 +518,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "dml_dev",
    "language": "python",
    "name": "python3"
   },
@@ -532,7 +532,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,

requirements.txt

@@ -1,5 +1,5 @@
 DoubleML[rdd]
-scikit-learn<1.6
+scikit-learn==1.6.1
 
 # test
 pytest