diff --git a/docs/hyperopt.md b/docs/hyperopt.md
index 51a6a5187..fdde74fb6 100644
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@@ -4,7 +4,7 @@ This page explains how to tune your strategy by finding the optimal
 parameters, a process called hyperparameter optimization. The bot uses algorithms included in the `scikit-optimize` package to accomplish this.
 The search will burn all your CPU cores, make your laptop sound like a fighter jet and still take a long time.
 
-In general, the search for best parameters starts with a few random combinations (see [below](#reproducible-results) for more details) and then uses Bayesian search with a ML regressor algorithm (currently ExtraTreesRegressor) to quickly find a combination of parameters in the search hyperspace that minimizes the value of the [loss function](#loss-functions).
+In general, the search for best parameters starts with a few random combinations (see [below](#reproducible-results) for more details) and then uses one of optuna's sampler algorithms (currently NSGAIIISampler) to quickly find a combination of parameters in the search hyperspace that minimizes the value of the [loss function](#loss-functions).
 
 Hyperopt requires historic data to be available, just as backtesting does (hyperopt runs backtesting many times with different parameters).
 To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation.
diff --git a/freqtrade/optimize/hyperopt/hyperopt_auto.py b/freqtrade/optimize/hyperopt/hyperopt_auto.py
index 1da80ec02..6fabaaf35 100644
--- a/freqtrade/optimize/hyperopt/hyperopt_auto.py
+++ b/freqtrade/optimize/hyperopt/hyperopt_auto.py
@@ -12,7 +12,7 @@ from freqtrade.exceptions import OperationalException
 
 
 with suppress(ImportError):
-    from skopt.space import Dimension
+    from freqtrade.optimize.space import Dimension
 
 from freqtrade.optimize.hyperopt.hyperopt_interface import EstimatorType, IHyperOpt
 
diff --git a/freqtrade/optimize/space/optunaspaces.py b/freqtrade/optimize/space/optunaspaces.py
index d574afe0f..9f152b991 100644
--- a/freqtrade/optimize/space/optunaspaces.py
+++ b/freqtrade/optimize/space/optunaspaces.py
@@ -34,9 +34,9 @@ class ft_IntDistribution(IntDistribution):
         **kwargs,
     ):
         self.name = name
-        self.low = low
-        self.high = high
-        return super().__init__(int(low), int(high), **kwargs)
+        self.low = int(low)
+        self.high = int(high)
+        return super().__init__(self.low, self.high, **kwargs)
 
     def __repr__(self):
         return f"IntDistribution(low={self.low}, high={self.high})"