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---
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- data-preprocessing
- automl
- benchmarks
size_categories:
- n<1K
- 1K<n<10K
- 10K<n<100K
- 100K<n<1M
dataset_info:
- config_name: imdb
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_examples: 18750
- name: test
num_examples: 25000
- name: validation
num_examples: 6250
- config_name: twenty_newsgroups
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: label_text
dtype: string
splits:
- name: train
num_examples: 8485
- name: test
num_examples: 7532
- name: validation
num_examples: 2829
- config_name: banking77
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_examples: 7502
- name: test
num_examples: 3080
- name: validation
num_examples: 2501
- config_name: trec
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_examples: 4089
- name: test
num_examples: 500
- name: validation
num_examples: 1363
- config_name: financial_phrasebank
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_examples: 1358
- name: test
num_examples: 453
- name: validation
num_examples: 453
- config_name: MASSIVE
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_examples: 11514
- name: test
num_examples: 2974
- name: validation
num_examples: 2033
configs:
- config_name: imdb
data_files:
- split: train
path: imdb/train.csv
- split: test
path: imdb/test.csv
- split: validation
path: imdb/validation.csv
- config_name: twenty_newsgroups
data_files:
- split: train
path: twenty_newsgroups/train.csv
- split: test
path: twenty_newsgroups/test.csv
- split: validation
path: twenty_newsgroups/validation.csv
- config_name: banking77
data_files:
- split: train
path: banking77/train.csv
- split: test
path: banking77/test.csv
- split: validation
path: banking77/validation.csv
- config_name: trec
data_files:
- split: train
path: trec/train.csv
- split: test
path: trec/test.csv
- split: validation
path: trec/validation.csv
- config_name: financial_phrasebank
data_files:
- split: train
path: financial_phrasebank/train.csv
- split: test
path: financial_phrasebank/test.csv
- split: validation
path: financial_phrasebank/validation.csv
- config_name: MASSIVE
data_files:
- split: train
path: MASSIVE/train.csv
- split: test
path: MASSIVE/test.csv
- split: validation
path: MASSIVE/validation.csv
---
# Data Preprocessing AutoML Benchmarks
This repository contains text classification datasets with known data quality issues for preprocessing research in AutoML.
## Usage
Load a specific dataset configuration like this:
```python
from datasets import load_dataset
# Example for loading the TREC dataset
dataset = load_dataset("MothMalone/data-preprocessing-automl-benchmarks", "trec")
```
## Available Datasets
Below are the details for each dataset configuration available in this repository.
Of course. Here are the completed descriptions for your dataset card.
### imdb
- Description: A large movie review dataset for binary sentiment classification, containing 25,000 highly polarized movie reviews for training and 25,000 for testing.
- Data Quality Issue: N/A
- Classes: 2
- Training Samples: 18750
- Validation Samples: 6250
- Test Samples: 25000
### twenty_newsgroups
- Description: A collection of approximately 20,000 newsgroup documents, partitioned evenly across 20 different newsgroups, making it a classic benchmark for text classification.
- Data Quality Issue: N/A
- Classes: 20
- Training Samples: 8485
- Validation Samples: 2829
- Test Samples: 7532
### banking77
- Description: A fine-grained dataset of 13,083 customer service queries from the banking domain, annotated with 77 distinct intents.
- Data Quality Issue: N/A
- Classes: 77
- Training Samples: 7502
- Validation Samples: 2501
- Test Samples: 3080
### trec
- Description: The Text REtrieval Conference (TREC) question classification dataset, containing questions categorized by their answer type (e.g., Person, Location, Number).
- Data Quality Issue: N/A
- Classes: 6
- Training Samples: 4089
- Validation Samples: 1363
- Test Samples: 500
### financial_phrasebank
- Description: A collection of sentences from English financial news, annotated for sentiment (positive, negative, or neutral) by financial experts.
- Data Quality Issue: N/A
- Classes: 3
- Training Samples: 1358
- Validation Samples: 453
- Test Samples: 453
-
### MASSIVE
- Description: A multilingual dataset of 1 million utterances for intent classification and slot filling, covering 52 languages. The en-US configuration is used here.
- Data Quality Issue: N/A
- Classes: 60
- Training Samples: 11514
- Validation Samples: 2033
- Test Samples: 2974
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