Please provide me your insights to resolve the below issue.
Error Details
Application Name : SCPortal
Minimum data per functionality : 25
Input File Name: /Users/Document/Desktop/PythonSpace/SC_Portal_Training_8thSep22.csv
Output file path: /Users/Document/Desktop/PythonSpace
Number of documents before filter: 0
Number of documents after filter: 0
SVC(C=100, gamma=0.001, probability=True)
Traceback (most recent call last):
File "machine_learning_oriflame_functionality_with_whole_data.py", line 403, in <module>
trainModel(inputFilePath, inputFileName, outputFilePath, applicationName, functionalityFieldName, cleanDataFieldName,minDataPerFunctionality)
File "machine_learning_oriflame_functionality_with_whole_data.py", line 232, in trainModel
svm_detector = pipeline_svm.fit(msg_train, label_train)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/pipeline.py", line 378, in fit
Xt = self._fit(X, y, **fit_params_steps)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/pipeline.py", line 336, in _fit
X, fitted_transformer = fit_transform_one_cached(
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/joblib/memory.py", line 349, in __call__
return self.func(*args, **kwargs)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/pipeline.py", line 870, in _fit_transform_one
res = transformer.fit_transform(X, y, **fit_params)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/feature_extraction/text.py", line 2079, in fit_transform
X = super().fit_transform(raw_documents)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/feature_extraction/text.py", line 1338, in fit_transform
vocabulary, X = self._count_vocab(raw_documents, self.fixed_vocabulary_)
File "/Users/Document/opt/anaconda3/lib/python3.8/site-packages/sklearn/feature_extraction/text.py", line 1228, in _count_vocab
raise ValueError(
ValueError: empty vocabulary; perhaps the documents only contain stop words