load_hlm#
- skfp.datasets.tdc.adme.load_hlm(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) DataFrame | tuple[list[str]] | ndarray#
Load the human subset of Human/Rat Liver Microsomal Stability dataset.
Liver microsomal stability or hepatic metabolic stability is an important property considered for the screening of drug candidates. The task is to determine whether the drug is stable or not [1] [2]. This subset relates to human liver microsomes.
See also
load_rlm()Tasks
1
Task type
classification
Total samples
6013
Recommended split
scaffold
Recommended metric
AUROC
- 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