[LightGBM] Weight column in LightGBM classifier is not working as per expectation

### SynapseML version

2.12:0.9.5

### System information

- **Language version** : python 3.7, scala 2.12
- **Spark Version**: 3.3.0
- **Spark Platform** : Databricks

### Describe the problem

Hi , I am using LightGBMClassifier for a skewed binary classification problem.
I have several features like A, B, C.... so on. I am grouping by the features and computing weights for class 0 and class 1.

However, for testing data I am giving weights as all 1s.

I can see my testing data's loss is not converging.
Is this the correct way to use weightCol feature ?

One more observation, while inferencing if I use `isUnbalance` as True , then the model gives random predictions , AUC comes down to 50%. So, I had to use `isUnbalance` as False while inferencing. Please let me know if this is the correct behavior.

### Code to reproduce issue

```
params = {'baggingFraction': 0.8156468375795559,
'featureFraction': 0.8609557255311693,
'featuresCol': 'features',
'labelCol': 'label',
'learningRate': 0.1449558170049662,
'maxDepth': 29,
'minSumHessianInLeaf': 0.03753901648224433,
'numIterations': 80,
'numLeaves': 133,
'weightCol': 'weight',
'objective': 'binary',
'useSingleDatasetMode': True,
'isUnbalance': False,
'useBarrierExecutionMode': True,
'parallelism': 'voting_parallel',
'metric': 'auc'
}

lgb = LightGBMClassifier(
numIterations = params['numIterations'],
numLeaves = params['numLeaves'],
maxDepth = params['maxDepth'],
baggingFraction = params['baggingFraction'],
featureFraction = params['featureFraction'],
minSumHessianInLeaf = params['minSumHessianInLeaf'],
learningRate=params['learningRate'],
objective = params['objective'],
labelCol = params['labelCol'],
featuresCol=params['featuresCol'],
weightCol=params['weightCol'],
useSingleDatasetMode=True,
#isUnbalance=False,
useBarrierExecutionMode=True,
#parallelism = "voting_parallel",
metric = params['metric']
)
```

### Other info / logs

_No response_

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

- [ ] `area/cognitive`: Cognitive project
- [ ] `area/core`: Core project
- [ ] `area/deep-learning`: DeepLearning project
- [X] `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?

- [ ] `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