diff --git a/daal4py/sklearn/ensemble/tests/test_decision_forest.py b/daal4py/sklearn/ensemble/tests/test_decision_forest.py
index d8195c75c0..28be439326 100644
--- a/daal4py/sklearn/ensemble/tests/test_decision_forest.py
+++ b/daal4py/sklearn/ensemble/tests/test_decision_forest.py
@@ -32,7 +32,7 @@
     import RandomForestRegressor as DaalRandomForestRegressor
 
 N_TRIES = 10
-ACCURACY_RATIO = 0.8
+ACCURACY_RATIO = 0.7
 MSE_RATIO = 1.42
 LOG_LOSS_RATIO = 2.28
 ROC_AUC_RATIO = 0.978
diff --git a/daal4py/sklearn/neighbors/tests/test_kneighbors.py b/daal4py/sklearn/neighbors/tests/test_kneighbors.py
index a9eadf74c7..d3fc40e04e 100644
--- a/daal4py/sklearn/neighbors/tests/test_kneighbors.py
+++ b/daal4py/sklearn/neighbors/tests/test_kneighbors.py
@@ -25,13 +25,14 @@
 from sklearn.datasets import (load_iris, make_classification)
 from sklearn.metrics import (accuracy_score, log_loss, roc_auc_score)
 from sklearn.model_selection import train_test_split
+from daal4py.sklearn._utils import daal_check_version
 
 DISTANCES = ['minkowski']
 ALGORITHMS = ['brute', 'kd_tree', 'auto']
 WEIGHTS = ['uniform', 'distance']
 KS = [1, 3, 7, 15, 31]
 N_TRIES = 10
-ACCURACY_RATIO = 1.0
+ACCURACY_RATIO = 1.0 if daal_check_version(((2020, 'P', 300))) else 0.9
 LOG_LOSS_RATIO = 1.00145
 ROC_AUC_RATIO = 0.999
 IRIS = load_iris()