Text Classification
Keras
English
movie-certification
movie-scripts
screenplay
mpaa-rating
age-rating
ordinal-classification
tf-idf
mlp
explainable-ai
english
ieee-gcat-2025
Instructions to use pratikkalamkar/moviecert-tfidf-unbalanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use pratikkalamkar/moviecert-tfidf-unbalanced with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://pratikkalamkar/moviecert-tfidf-unbalanced") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| datasets: | |
| - pratikkalamkar/UnBalanced_Hollywood_Movies_Scripts_Age_Rating_Dataset_1142 | |
| language: | |
| - en | |
| pipeline_tag: text-classification | |
| library_name: keras | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| - mae | |
| tags: | |
| - movie-certification | |
| - movie-scripts | |
| - screenplay | |
| - mpaa-rating | |
| - age-rating | |
| - ordinal-classification | |
| - tf-idf | |
| - mlp | |
| - explainable-ai | |
| - english | |
| - ieee-gcat-2025 | |
| # TF-IDF + Multi-Layer Perceptron for MPAA Age Rating Prediction | |
| This repository contains a **TF-IDF + Multi-Layer Perceptron (MLP)** model trained on the **Unbalanced Hollywood Movie Scripts Age Rating Dataset (1,142 scripts)** for automated **MPAA age rating prediction** from full-length English movie scripts. | |
| The model was developed as part of the following publication: | |
| > **Hierarchical Ordinal Framework for Automated Movie Censorship Using Full-Length Scripts** | |
| ## Dataset | |
| - **Unbalanced Hollywood Movie Scripts Age Rating Dataset (1,142)** | |
| - 1,142 English movie scripts | |
| - Five MPAA age rating categories: | |
| - G | |
| - PG | |
| - PG-13 | |
| - R | |
| - NC-17 | |
| Dataset: | |
| https://huggingface.co/datasets/pratikkalamkar/UnBalanced_Hollywood_Movies_Scripts_Age_Rating_Dataset_1142 | |
| ## Task | |
| Predict the appropriate MPAA age rating for a complete English movie script using TF-IDF features and a Multi-Layer Perceptron classifier. | |
| ## Citation | |
| If you use this model in your research, please cite: | |
| ```bibtex | |
| @inproceedings{kalamkar2025hierarchical, | |
| author = {Pratik N. Kalamkar and Yogesh K. Sharma}, | |
| title = {Hierarchical Ordinal Framework for Automated Movie Censorship Using Full-Length Scripts}, | |
| booktitle = {2025 IEEE 6th Global Conference for Advancement in Technology (GCAT)}, | |
| year = {2025}, | |
| pages = {1--7}, | |
| doi = {10.1109/GCAT66372.2025.11368510} | |
| } | |
| ``` | |
| or | |
| P. N. Kalamkar and Y. K. Sharma, "Hierarchical Ordinal Framework for Automated Movie Censorship Using Full-Length Scripts," 2025 IEEE 6th Global Conference for Advancement in Technology (GCAT), Bangalore, India, 2025, pp. 1-7, doi: 10.1109/GCAT66372.2025.11368510. | |
| ## License | |
| Apache License 2.0 |