QSAR oral toxicity
Donated on 9/30/2019
Data set containing values for 1024 binary attributes (molecular fingerprints) used to classify 8992 chemicals into 2 classes (very toxic/positive, not very toxic/negative)
Dataset Characteristics
Multivariate
Subject Area
Physical Science
Associated Tasks
Classification
Feature Type
-
# Instances
8992
# Features
1024
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Citation
QSAR oral toxicity. (2019). UCI Machine Learning Repository. https://doi.org/10.24432/C5PS4J.
BibTeX
@misc{misc_qsar_oral_toxicity_508,
title = {{QSAR oral toxicity}},
year = {2019},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5PS4J}
}Install the ucimlrepo package
pip install ucimlrepo
Import the dataset into your code
View the full documentationfrom ucimlrepo import fetch_ucirepo # fetch dataset qsar_oral_toxicity = fetch_ucirepo(id=508) # data (as pandas dataframes) X = qsar_oral_toxicity.data.features y = qsar_oral_toxicity.data.targets # metadata print(qsar_oral_toxicity.metadata) # variable information print(qsar_oral_toxicity.variables)
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.