[BUG] Unable to save a trained Isolation Forest model in SynapseML

### SynapseML version

0.10.1

### System information

- **Language version** (e.g. python 3.8, scala 2.12): Python 3.10.8
- **Spark Version** (e.g. 3.2.3): Spark 3.2.2
- **Spark Platform** (e.g. Synapse, Databricks): Synapse

### Describe the problem

I'm trying to save an Isolation Forest model after training in SynapseML. However, errors occur, and the save method does not work.

### Code to reproduce issue

~~~python
# building a model
from synapse.ml.isolationforest import *
from pyspark.ml.feature import VectorAssembler

# Isolation Forest parameters
contamination = 0.021
num_estimators = 100
max_samples = 100
max_features = 1.0

# Model Setup
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)
)

# Training
va=VectorAssembler(inputCols=inputCols, outputCol="features")
train_data = va.transform(sdf_train)
model_isolationforest_trained = isolationForest.fit(train_data)

# Predictions
test_data = va.transform(sdf_test)
pred = model_isolationforest_trained.transform(test_data)

# Saving
model_isolationforest_trained.write().overwrite().save("path")
~~~

### Other info / logs

The part of the errors caused from `model_isolationforest_trained.write().overwrite().save("path")` is like
~~~python
output Error:
py4JJavaError: An error occured while calling 03919.save: org.apache.spark.SparkException: Job aborted. ~~

Caused by: java.lang.NoSuchMethodError: 'scala.Function1 orgz.apache.spark.sql.execution.datasources.DataSourceUtils$.createDateRebaseFucInWirte(scala.Enumeration$Value, java.lang.String)' ~~
~~~

Does the error imply that we cannot save the trained Isolation Forest model in the SynapseML? As a side note, I confirmed that the save method works with the LightGBMClassifier in the SynapseML.
I would appreciate it if someone could provide any solutions.

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

- [ ] `area/cognitive`: Cognitive project
- [X] `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
- [ ] `area/models`: models related issue

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

- [X] `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?

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

Start with the IsolationForest training and model_isolationforest_trained.write().overwrite().save("path") reproduction using SynapseML 0.10.1, Python 3.10.8, and Spark 3.2.2. Investigate the reported DataSourceUtils NoSuchMethodError and compare this persistence path with the working LightGBMClassifier save path. Done means a trained Isolation Forest model can be saved successfully in the reported Synapse environment.

Written by the indexing model from the issue text.