Model: mastefan/2025-24679-tabular-autolguon-predictor
Author: mastefan
Pipeline: table-question-answering
Tags: books,, tabular_data,, classification,, classroom,, table-question-answering, en, dataset:jennifee/HW1-tabular-dataset, license:mit, region:us
Card metadata: name: Tabular Predictor - Books
datasets: jennifee/HW1-tabular-dataset
language: en
model_info: Author: Michael Stefanov
Purpose: This model to be used for in-class assignments and activity associated with Course 24679 at CMU.
Preprocessing/Augmentation: The preprocessing of this data includes splitting the dataset into train and test, and using autoML to predict whether the book from the dataset will be reccomended The peredictor weas fitting using a 20 minute time limit, in addition to a best_quality present and auto_stacking to improve accuracy over the constrained timeframe. 
Intented use/limits: The intended use of this dataset is exclusively for classroom and assignment use. Please request permission if you wish to use it elsewhere
ethical notes: The AI used in this sample is a fairly benign use case handling basic tabular manipulation. However, please review the environmental impacts of large-scale usage in exchange for implementing the necessary good such technology brings.
limitations: Dataset trained on is a simple tabular dataset for books, and has been trained to classify the reccomended column which is a simple binary. This training model is quite minimal as a result
license: mit
AI Usage disclosure: Original code to assist with data augmentation was developed with use of Google Gemini in combination with course material from 24679 at CMU
license: mit
metrics: accuracy
pipeline_tag: table-question-answering
tags: books,, tabular_data,, classification,, classroom,
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Created: 2025-09-22 04:59:58