ICEExplainer returns same feature importance

### SynapseML version

Version: 0.11.0

### System information

10.4 LTS ML (includes Apache Spark 3.2.1, Scala 2.12)
com.microsoft.azure:synapseml_2.12:0.10.1
pyspark in databricks

### Describe the problem

In my randomforesstclassification model, which is pyspark model....all the features are numerical..

the ouptut

### Code to reproduce issue

pdp_1 = ICETransformer(
model=model_object_1,
targetCol="probability",
kind="average",
targetClasses=[1],
numericFeatures=[{"name": "pd1_amount_join", "numSplits": 50, "rangeMin": 0.0, "rangeMax": 400000.0}]
#convert -290 to -1
)

output_pdp_1 = pdp_1.transform(features_1.filter(features_1.days_inactive == 0))
display(output_pdp_1)

#Below is the code which is showing error
df_userid_1 = get_pandas_df_from_column(output_pdp_1, "pd1_amount_join_dependence")
plot_dependence_for_numeric(df_userid_1, "pd1_amount_join")

### Other info / logs

**1st display result ->**
{"264000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "0.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "400000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "80000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "336000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "56000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "32000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "384000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "24000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "152000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "72000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "248000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "160000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "176000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "200000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "296000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "368000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "376000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "168000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "64000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "184000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "240000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "88000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "360000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "320000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "256000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "352000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "136000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "8000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "312000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "16000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "192000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "216000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "232000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "272000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "104000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "392000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "224000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "128000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "288000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "344000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "208000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "40000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "96000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "280000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "112000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "48000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "144000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "304000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "328000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}, "120000.0": {"vectorType": "dense", "length": 1, "values": [0.34720682012802506]}}

**2nd error ->**

/databricks/spark/python/pyspark/sql/pandas/conversion.py:92: UserWarning: toPandas attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true; however, failed by the reason below:
Unable to convert the field 104000.0. If this column is not necessary, you may consider dropping it or converting to primitive type before the conversion.
Direct cause: Unsupported type in conversion to Arrow: VectorUDT
Attempting non-optimization as 'spark.sql.execution.arrow.pyspark.fallback.enabled' is set to true.
warnings.warn(msg)
ValueError: invalid literal for int() with base 10: '104000.0'

### 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
- [X] `area/website`: Website
- [ ] `area/build`: Project build system
- [X] `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
- [X] `integrations/databricks`: Databricks integrations