multi-classification
multi-temporal-crop-classification
Dataset Card for Multi-Temporal Crop Classification
Dataset Summary
This dataset contains temporal Harmonized Landsat-Sentinel imagery of diverse land cover and crop type classes across the Contiguous United States for the year 2022. The target labels are derived from USDA's Crop Data Layer (CDL). It's primary purpose is for training segmentation geospatial machine learning models.
Dataset Structure
TIFF Files
Each tiff file covers a… See the full description on the dataset page: https://huggingface.co/datasets/ibm-nasa-geospatial/multi-temporal-crop-classification.multi-label-class-github-issues-text-classification
Dataset Card for "multi-label-class-github-issues-text-classification"
More Information needed
multi-domain-document-classification
multi_domain_document_classification
Multi-domain document classification datasets.
Biomedical: chemprot, rct-sample
Computer Science: citation_intent, sciie
Customer Review: amcd, yelp_review
Social Media: tweet_eval_irony, tweet_eval_hate, tweet_eval_emotion
The yelp_review dataset is randomly downsampled to 2000/2000/8000 for test/validation/train.
chemprot
citation_intent
hyperpartisan_news
rct_sample
sciie
amcd
yelp_review
tweet_eval_irony
tweet_eval_hate… See the full description on the dataset page: https://huggingface.co/datasets/asahi417/multi-domain-document-classification.task1577_amazon_reviews_multi_japanese_language_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1577_amazon_reviews_multi_japanese_language_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1577_amazon_reviews_multi_japanese_language_classification.wos_hierarchical_multi_label_text_classificationIntroduced by du Toit and Dunaiski (2024) Introducing Three New Benchmark Datasets for Hierarchical Text Classification.
The WOS Hierarchical Text Classification are three dataset variants created from Web of Science (WOS) title and abstract data categorised into a hierarchical, multi-label class structure. The aim of the sampling and filtering methodology used was to create well-balanced class distributions (at chosen hierarchical levels). Furthermore, the WOS_JTF variant was also created… See the full description on the dataset page: https://huggingface.co/datasets/marcelsun/wos_hierarchical_multi_label_text_classification.Multi-Lingual-Lyrics-for-Genre-Classificationfrom https://www.kaggle.com/datasets/mateibejan/multilingual-lyrics-for-genre-classification