load_ld50_zhu#
- skfp.datasets.tdc.tox.load_ld50_zhu(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) DataFrame | tuple[list[str]] | ndarray#
Load the Acute Toxicity LD50 dataset.
Acute toxicity LD50 measures the most conservative dose that can lead to lethal adverse effects [1] [2]. The regression task is to predict the acute toxicity of drugs.
Tasks
1
Task type
regression
Total samples
7385
Recommended split
scaffold
Recommended metric
MAE
- Parameters:
data_dir ({None, str, path-like}, default=None) – Path to the root data directory. If
None, currently set scikit-learn directory is used, by default $HOME/scikit_learn_data.as_frame (bool, default=False) – If True, returns the raw DataFrame with columns: “SMILES”, “label”. Otherwise, returns SMILES as list of strings, and labels as a NumPy array (1D integer binary vector).
verbose (bool, default=False) – If True, progress bar will be shown for downloading or loading files.
- Returns:
data – Depending on the
as_frameargument, one of: - Pandas DataFrame with columns: “SMILES”, “label” - tuple of: list of strings (SMILES), NumPy array (labels)- Return type:
pd.DataFrame or tuple(list[str], np.ndarray)
References