Issue
I have code to training the model for multi class text classification
and it's work but I can't use that model. this is my code for training
def training(df):
X = df.Text
y = df.Tags
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
lr = Pipeline([('vect', CountVectorizer()),
('tfidf', TfidfTransformer()),
('clf', LogisticRegression()),
])
lr.fit(X_train, y_train)
y_pred1 = lr.predict(X_test)
print(f"Accuracy is : {accuracy_score(y_pred1, y_test)}")
print(lr.predict('ماست کم چرب 900 گرمی رامک'))
when I run the code got this this result Accuracy is : 0.9957983193277311
and this error
Traceback (most recent call last): File "E:\Python\NLP Project\Beta_00\Level0\handleClassification.py", line 100, in training(df)
File "E:\Python\NLP Project\Beta_00\Level0\handleClassification.py", line 85, in training print(lr.predict('ماست کم چرب 900 گرمی رامک'))
File "E:\Python\NLP Project\Beta_00\venv\lib\site-packages\sklearn\utils\metaestimators.py" line 120, in out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
File "E:\Python\NLP Project\Beta_00\venv\lib\site-packages\sklearn\pipeline.py", line 418, in predict Xt = transform.transform(Xt)
File "E:\Python\NLP Project\Beta_00\venv\lib\site-
packages\sklearn\feature_extraction\text.py", line 1248, in transform raise ValueError( ValueError: Iterable over raw text documents expected, string object received.
Solution
Below lines need correction:
lr.fit(X_train, y_train)
y_pred1 = lr.predict(X_test)
print(f"Accuracy is : {accuracy_score(y_test, y_pred1)}") #<--- here
print(lr.predict(['ماست کم چرب 900 گرمی رامک'])) #<--- here
The line lr.predict(input)
should take in an input of 'array' type.
Answered By - perpetualstudent
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