---
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