This package is for Text Classification of NLP Task
Project description
No Code Text Classifier Tool
This tool will help you to perform training, evaluation & prediction of Text Classification task without knowing any kind of code. You have to define the dataset directory and create your model and perform predictions without any issue. In the backend, this will automatically perform text preprocessing, model training etc. You can also perform hyperparameter techniques to get the best model through experiments. Let's get started.
Install the pakage
pip install NoCodeTextClassifier
Training the Text Classification
Define the datapath
data_path = "dataset.csv"
Clean the Text dataset and transform the label into number
# It will take datapath, text feature and target feature
process = process(data_path,'email','class')
df = process.processing()
print(df.head())
Convert the text feature into numerical vector. You can apply multiple vectorization such as TfIdfVectorizer, CountVectorizer.
Vectorization = Vectorization(df,'clean_text')
TfidfVectorizer = Vectorization.TfidfVectorizer(max_features= 10000)
print(TfidfVectorizer.toarray())
Split the dataset into training and testing
X_train, X_test, y_train, y_test = process.split_data(TfidfVectorizer.toarray(), df['labeled_target'])
print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)
Perform training with various models such as Naive Bayers, Decision Tree, Logistic Regression, and others. After training, you will see the evalution of the trained model.
models = Models(X_train=X_train,X_test = X_test, y_train = y_train, y_test = y_test)
models.DecisionTree()
For Inferencing with text data
For prediction of the text data with the trained model, try this.
text = input("Enter your text:\n")
inference.prediction(text)
Author:
Md Abdullah Al Hasib
Thank YOU
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