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TF-IDF + LogReg baseline for text classification

Project description

Text Classification Baseline

Pipeline for building text classification TF-IDF + LogReg baselines using sklearn.

Usage

Instead of writing custom code for specific text classification task, you just need:

  1. install pipeline:
pip install text-classification-baseline
  1. run pipeline:

    • either in terminal:
    text-clf --config config.yaml
    
    • or in python:
    import text_clf
    
    text_clf.train(path_to_config="config.yaml")
    

No data preparation is needed, only a csv file with two raw columns (with arbitrary names):

  • text
  • target

NOTE: the target can be presented in any format, including text - not necessarily integers from 0 to n_classes-1.

Config

The user interface consists of only one file config.yaml.

Change config.yaml to create the desired configuration and train text classification model.

Default config.yaml:

seed: 42
verbose: true
path_to_save_folder: models

# data
data:
  train_data_path: data/train.csv
  valid_data_path: data/valid.csv
  sep: ','
  text_column: text
  target_column: target_name_short

# tf-idf
tf-idf:
  lowercase: true
  ngram_range: (1, 1)
  max_df: 1.0
  min_df: 0.0

# logreg
logreg:
  penalty: l2
  C: 1.0
  class_weight: balanced
  solver: saga
  multi_class: auto
  n_jobs: -1

Output

After training the model, the pipeline will return the following files:

  • model.joblib - sklearn pipeline with TF-IDF and LogReg steps
  • target_names.json - mapping from encoded target labels from 0 to n_classes-1 to it names
  • config.yaml - config that was used to train the model
  • logging.txt - logging file

Requirements

Python >= 3.7

Citation

If you use text-classification-baseline in a scientific publication, we would appreciate references to the following BibTex entry:

@misc{dayyass2021textclf,
    author       = {El-Ayyass, Dani},
    title        = {Pipeline for training text classification baselines},
    howpublished = {\url{https://github.com/dayyass/text-classification-baseline}},
    year         = {2021}
}

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