Spelling python plugin (#10525)

2 files changed, 3 insertions, 3 deletions

diff --git a/collectors/python.d.plugin/anomalies/anomalies.chart.py b/collectors/python.d.plugin/anomalies/anomalies.chart.py
index 3691537b4b..97dbb1d1ed 100644
--- a/collectors/python.d.plugin/anomalies/anomalies.chart.py
+++ b/collectors/python.d.plugin/anomalies/anomalies.chart.py
@@ -117,7 +117,7 @@ class Service(SimpleService):
         self.model_display_names = {model: model.split('::')[1] if '::' in model else model for model in self.models_in_scope}
 
     def model_params_init(self):
-        """Model paramaters initialisation.
+        """Model parameters initialisation.
         """
         self.train_max_n = self.configuration.get('train_max_n', 100000)
         self.train_n_secs = self.configuration.get('train_n_secs', 14400)
diff --git a/collectors/python.d.plugin/anomalies/anomalies.conf b/collectors/python.d.plugin/anomalies/anomalies.conf
index 586a277ea9..9950534aaa 100644
--- a/collectors/python.d.plugin/anomalies/anomalies.conf
+++ b/collectors/python.d.plugin/anomalies/anomalies.conf
@@ -92,7 +92,7 @@ local:
     diffs_n: 1
 
     # What is the typical proportion of anomalies in your data on average? 
-    # This paramater can control the sensitivity of your models to anomalies. 
+    # This parameter can control the sensitivity of your models to anomalies. 
     # Some discussion here: https://github.com/yzhao062/pyod/issues/144
     contamination: 0.001
 
@@ -100,7 +100,7 @@ local:
     # just the average of all anomaly probabilities at each time step
     include_average_prob: true
 
-    # Define any custom models you would like to create anomaly probabilties for, some examples below to show how.
+    # Define any custom models you would like to create anomaly probabilities for, some examples below to show how.
     # For example below example creates two custom models, one to run anomaly detection user and system cpu for our demo servers
     # and one on the cpu and mem apps metrics for the python.d.plugin.
     # custom_models: