[BUG] Isolation Forest java.lang.ClassCastException

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### SynapseML version

1.0.4

### System information

- **Language version**: python 3.8 , scala 2.12
- **Spark Version**: 3.5.0
- **Spark Platform**): on-premise

### Describe the problem

I'm currently trying to train an Isolation Forest model.
However, when I try to run pipeline.fit() the execution aborts after some stages with an exception I have no idea about what is going wrong:
java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.BoundReference.accessor of type scala.Function2 in instance of org.apache.spark.sql.catalyst.expressions.BoundReference

Have had anyone else some similar issues?

### Code to reproduce issue

I'm currently doing the same like in the documentation examples:
# Isolation Forest Parameter
contamination = 0.01
num_estimators = 1
max_samples = 1
max_features = 1.0

# MLFlow Experiment
artifact_path = "isolation_forest"
experiment_name = f"/opt/spark-data/iforest/isolation_forest_experiment{str(uuid.uuid1())}/"
model_name = f"isolation-forest-model-v1"

# Isolation Forest Model
isolationForest = IsolationForest() \
.setNumEstimators(num_estimators) \
.setBootstrap(False) \
.setMaxSamples(max_samples) \
.setMaxFeatures(max_features) \
.setFeaturesCol("features") \
.setPredictionCol("predictedLabel") \
.setScoreCol("outlierScore") \
.setContamination(contamination) \
.setContaminationError(0.01 * contamination) \
.setRandomSeed(1)

mlflow.set_experiment(experiment_name)
with mlflow.start_run():
va = VectorAssembler(inputCols=inputCols, outputCol="features")
pipeline = Pipeline(stages=[va, isolationForest])
model = pipeline.fit(df_train)
mlflow.spark.log_model(
model, artifact_path=artifact_path, registered_model_name=model_name
)

### Other info / logs

```
24/06/07 12:17:19 WARN TaskSetManager: Lost task 0.0 in stage 9.0 (TID 1037) (172.20.0.6 executor 1): java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.BoundReference.accessor of type scala.Function2 in instance of org.apache.spark.sql.catalyst.expressions.BoundReference
at java.base/java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(Unknown Source)
at java.base/java.io.ObjectStreamClass$FieldReflector.checkObjectFieldValueTypes(Unknown Source)
at java.base/java.io.ObjectStreamClass...
...
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.base/java.lang.Thread.run(Unknown Source)
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
Cell In[28], line 5
3 va = VectorAssembler(inputCols=inputCols, outputCol="features")
4 pipeline = Pipeline(stages=[va, isolationForest])
----> 5 model = pipeline.fit(df_train)
6 mlflow.spark.log_model(
7 model, artifact_path=artifact_path, registered_model_name=model_name
8 )

File /usr/local/lib/python3.10/site-packages/pyspark/ml/base.py:205, in Estimator.fit(self, dataset, params)
203 return self.copy(params)._fit(dataset)
204 else:
--> 205 return self._fit(dataset)
206 else:
207 raise TypeError(
208 "Params must be either a param map or a list/tuple of param maps, "
209 "but got %s." % type(params)
210 )

File /usr/local/lib/python3.10/site-packages/pyspark/ml/pipeline.py:134, in Pipeline._fit(self, dataset)
132 dataset = stage.transform(dataset)
133 else: # must be an Estimator
--> 134 model = stage.fit(dataset)
135 transformers.append(model)
136 if i < indexOfLastEstimator:

File /usr/local/lib/python3.10/site-packages/pyspark/ml/base.py:205, in Estimator.fit(self, dataset, params)
203 return self.copy(params)._fit(dataset)
204 else:
--> 205 return self._fit(dataset)
206 else:
207 raise TypeError(
208 "Params must be either a param map or a list/tuple of param maps, "
209 "but got %s." % type(params)
210 )

File /tmp/spark-d3e18495-1dca-4d82-af1b-2b8ad9c97eee/userFiles-ad8359f8-030f-45fb-b8ee-0cd05a246fe7/com.microsoft.azure_synapseml-core_2.12-1.0.4.jar/synapse/ml/isolationforest/IsolationForest.py:309, in IsolationForest._fit(self, dataset)
308 def _fit(self, dataset):
--> 309 java_model = self._fit_java(dataset)
310 return self._create_model(java_model)

File /usr/local/lib/python3.10/site-packages/pyspark/ml/wrapper.py:378, in JavaEstimator._fit_java(self, dataset)
375 assert self._java_obj is not None
377 self._transfer_params_to_java()
--> 378 return self._java_obj.fit(dataset._jdf)

File /usr/local/lib/python3.10/site-packages/py4j/java_gateway.py:1322, in JavaMember.__call__(self, *args)
1316 command = proto.CALL_COMMAND_NAME +\
1317 self.command_header +\
1318 args_command +\
1319 proto.END_COMMAND_PART
1321 answer = self.gateway_client.send_command(command)
-> 1322 return_value = get_return_value(
1323 answer, self.gateway_client, self.target_id, self.name)
1325 for temp_arg in temp_args:
1326 if hasattr(temp_arg, "_detach"):

File /usr/local/lib/python3.10/site-packages/pyspark/errors/exceptions/captured.py:179, in capture_sql_exception..deco(*a, **kw)
177 def deco(*a: Any, **kw: Any) -> Any:
178 try:
--> 179 return f(*a, **kw)
180 except Py4JJavaError as e:
181 converted = convert_exception(e.java_exception)

File /usr/local/lib/python3.10/site-packages/py4j/protocol.py:326, in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
331 "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
332 format(target_id, ".", name, value))

Py4JJavaError: An error occurred while calling o119.fit.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 9.0 failed 4 times, most recent failure: Lost task 0.3 in stage 9.0 (TID 1040) (172.20.0.7 executor 0): java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.BoundReference.accessor of type scala.Function2 in instance of org.apache.spark.sql.catalyst.expressions.BoundReference
...
```

### What component(s) does this bug affect?

- [ ] `area/cognitive`: Cognitive project
- [ ] `area/core`: Core project
- [ ] `area/deep-learning`: DeepLearning project
- [ ] `area/lightgbm`: Lightgbm project
- [ ] `area/opencv`: Opencv project
- [ ] `area/vw`: VW project
- [ ] `area/website`: Website
- [ ] `area/build`: Project build system
- [ ] `area/notebooks`: Samples under notebooks folder
- [ ] `area/docker`: Docker usage
- [X] `area/models`: models related issue

### What language(s) does this bug affect?

- [ ] `language/scala`: Scala source code
- [X] `language/python`: Pyspark APIs
- [ ] `language/r`: R APIs
- [ ] `language/csharp`: .NET APIs
- [ ] `language/new`: Proposals for new client languages

### What integration(s) does this bug affect?

- [ ] `integrations/synapse`: Azure Synapse integrations
- [ ] `integrations/azureml`: Azure ML integrations
- [ ] `integrations/databricks`: Databricks integrations

Reproduce the failure using the IsolationForest pipeline shown in the issue with SynapseML 1.0.4, Python 3.8, Scala 2.12, and Spark 3.5.0. Start at the IsolationForest.py _fit path named in the traceback and inspect the models-related implementation; done means pipeline.fit completes without the reported ClassCastException and a regression test covers the configuration.

Written by the indexing model from the issue text.