Datasets:
sms_spam

- {"plain_text": {"description": "The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.\nIt has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.\n", "citation": "@inproceedings{Almeida2011SpamFiltering,\n title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},\n author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},\n year={2011},\n booktitle = \"Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)\",\n}\n", "homepage": "http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection", "license": "", "features": {"sms": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["ham", "spam"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "sms", "output": "label"}, "task_templates": [{"task": "text-classification", "text_column": "sms", "label_column": "label", "labels": ["ham", "spam"]}], "builder_name": "sms_spam", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 521756, "num_examples": 5574, "dataset_name": "sms_spam"}}, "download_checksums": {"http://archive.ics.uci.edu/ml/machine-learning-databases/00228/smsspamcollection.zip": {"num_bytes": 203415, "checksum": "1587ea43e58e82b14ff1f5425c88e17f8496bfcdb67a583dbff9eefaf9963ce3"}}, "download_size": 203415, "post_processing_size": null, "dataset_size": 521756, "size_in_bytes": 725171}}