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microsoft · Nov 30, 2022 · 1918ae6 · 1918ae6
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diff --git a/website/docs/features/lightgbm/about.md b/website/docs/features/lightgbm/about.md
@@ -57,11 +57,12 @@ model = LightGBMRegressor(application='quantile',
 For an end to end application, check out the LightGBM [notebook
 example](../LightGBM%20-%20Overview).
 
-### Arguments
+### Arguments/Parameters
 
 SynapseML exposes getters/setters for many common LightGBM parameters.
 In python, you can use the properties as shown above, or in Scala use the
 fluent setters.
+
 ```scala
 import com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier
 val classifier = new LightGBMClassifier()
@@ -74,13 +75,15 @@ need to set some parameters that SyanpseML does not expose a setter for, use
 passThroughArgs. This is just a free string that you can use to add extra parameters
 to the command SynapseML sends to configure LightGBM.
 
+In python:
 ```python
 from synapse.ml.lightgbm import LightGBMClassifier
-model = LightGBMClassifier(passThroughArgs="force_row_wise=true",
+model = LightGBMClassifier(passThroughArgs="force_row_wise=true min_sum_hessian_in_leaf=2e-3",
                            numIterations=100,
                            numLeaves=31).fit(train)
 ```
 
+In Scala:
 ```scala
 import com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier
 val classifier = new LightGBMClassifier()
@@ -93,7 +96,7 @@ For formatting options and specific argument documentation, see
 [LightGBM docs](https://lightgbm.readthedocs.io/en/v3.3.2/Parameters.html). Some
 parameters SynapseML will set specifically for the Spark distributed environment and
 should not be changed. Some parameters are for cli mode only, and will not work within
-Spark.
+Spark. 
 
 Note that you can mix passThroughArgs and explicit args, as shown above. SynapseML will
 merge them to create one argument string to send to LightGBM. If you set a parameter in

diff --git a/website/versioned_docs/version-0.10.0/features/lightgbm/about.md b/website/versioned_docs/version-0.10.0/features/lightgbm/about.md
@@ -57,7 +57,7 @@ model = LightGBMRegressor(application='quantile',
 For an end to end application, check out the LightGBM [notebook
 example](../LightGBM%20-%20Overview).
 
-### Arguments
+### Arguments/Parameters
 
 SynapseML exposes getters/setters for many common LightGBM parameters.
 In python, you can use the properties as shown above, or in Scala use the
@@ -74,13 +74,15 @@ need to set some parameters that SyanpseML does not expose a setter for, use
 passThroughArgs. This is just a free string that you can use to add extra parameters
 to the command SynapseML sends to configure LightGBM.
 
+In python:
 ```python
 from synapse.ml.lightgbm import LightGBMClassifier
-model = LightGBMClassifier(passThroughArgs="force_row_wise=true",
+model = LightGBMClassifier(passThroughArgs="force_row_wise=true min_sum_hessian_in_leaf=2e-3",
                            numIterations=100,
                            numLeaves=31).fit(train)
 ```
 
+In Scala:
 ```scala
 import com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier
 val classifier = new LightGBMClassifier()

diff --git a/website/versioned_docs/version-0.10.1/features/lightgbm/about.md b/website/versioned_docs/version-0.10.1/features/lightgbm/about.md
@@ -57,7 +57,7 @@ model = LightGBMRegressor(application='quantile',
 For an end to end application, check out the LightGBM [notebook
 example](../LightGBM%20-%20Overview).
 
-### Arguments
+### Arguments/Parameters
 
 SynapseML exposes getters/setters for many common LightGBM parameters.
 In python, you can use the properties as shown above, or in Scala use the
@@ -74,13 +74,15 @@ need to set some parameters that SyanpseML does not expose a setter for, use
 passThroughArgs. This is just a free string that you can use to add extra parameters
 to the command SynapseML sends to configure LightGBM.
 
+In python:
 ```python
 from synapse.ml.lightgbm import LightGBMClassifier
-model = LightGBMClassifier(passThroughArgs="force_row_wise=true",
+model = LightGBMClassifier(passThroughArgs="force_row_wise=true min_sum_hessian_in_leaf=2e-3",
                            numIterations=100,
                            numLeaves=31).fit(train)
 ```
 
+In Scala:
 ```scala
 import com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier
 val classifier = new LightGBMClassifier()

diff --git a/website/versioned_docs/version-0.10.2/features/lightgbm/about.md b/website/versioned_docs/version-0.10.2/features/lightgbm/about.md
@@ -57,7 +57,7 @@ model = LightGBMRegressor(application='quantile',
 For an end to end application, check out the LightGBM [notebook
 example](../LightGBM%20-%20Overview).
 
-### Arguments
+### Arguments/Parameters
 
 SynapseML exposes getters/setters for many common LightGBM parameters.
 In python, you can use the properties as shown above, or in Scala use the
@@ -74,13 +74,15 @@ need to set some parameters that SyanpseML does not expose a setter for, use
 passThroughArgs. This is just a free string that you can use to add extra parameters
 to the command SynapseML sends to configure LightGBM.
 
+In python:
 ```python
 from synapse.ml.lightgbm import LightGBMClassifier
-model = LightGBMClassifier(passThroughArgs="force_row_wise=true",
+model = LightGBMClassifier(passThroughArgs="force_row_wise=true min_sum_hessian_in_leaf=2e-3",
                            numIterations=100,
                            numLeaves=31).fit(train)
 ```
 
+In Scala:
 ```scala
 import com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassifier
 val classifier = new LightGBMClassifier()