license: apache-2.0
task_categories:
- text-classification
language:
- tr
size_categories:
- 1K<n<10K
Complaint Classification Dataset
Welcome to the complaint-classification-dataset
! This dataset is designed for the classification of text complaints into various categories. It is hosted on Hugging Face and is ideal for training machine learning models to categorize textual complaints.
Overview
This dataset contains text complaints and their associated categories, sourced from Trendyol and Şikayetvar, popular platforms for online shopping and consumer complaints in Turkey. It is a valuable resource for natural language processing (NLP) tasks, specifically for text classification and sentiment analysis.
Dataset Details
- Dataset Name:
complaint-classification-dataset
- Creator:
nanelimon
- Hugging Face URL: Complaint Classification Dataset
Data Sources
- Trendyol: A major e-commerce platform in Turkey.
- Şikayetvar: A popular complaint and review platform in Turkey.
Features
The dataset includes the following features:
- text: The complaint text that needs to be classified.
- label: The classification label assigned to the complaint text.
Data Format
The dataset is available in CSV format. Each row contains:
- text: The text of the complaint.
- label: The category label.
Example:
text | category |
---|---|
rezalet bir ürün | 1 |
bayıldım mükemmel | 0 |
Getting Started
To use this dataset in your project, follow these steps:
Using the Dataset with Hugging Face Datasets Library
Install the Datasets Library
If you haven’t already, install the
datasets
library from Hugging Face:pip install datasets
Load the Dataset
Use the following code to load the dataset:
from datasets import load_dataset dataset = load_dataset("nanelimon/complaint-classification-dataset")
Usage Examples
Text Classification
Here's a simple example of how to use this dataset for text classification:
from transformers import pipeline
# Load the dataset
from datasets import load_dataset
dataset = load_dataset("nanelimon/complaint-classification-dataset")
# Initialize a text classification pipeline
classifier = pipeline("text-classification")
# Sample text for classification
text = "Ürün hasarlı olarak elime ulaştı."
# Perform classification
result = classifier(text)
print(result)
License
The dataset is provided under the license specified by the creator. Please refer to the dataset card on Hugging Face for more details.
Contributing
If you have suggestions or improvements, please feel free to open an issue or submit a pull request. Contributions are always welcome!
Contact
For any questions or further information, you can reach out to the dataset creator: