load_chembl1871_ki#
- skfp.datasets.moleculeace.load_chembl1871_ki(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False, force_update: bool = False) DataFrame | tuple[list[str], ndarray]#
Load the ChEMBL1871 Ki dataset.
The task is to predict the inhibitor constant (Ki) of molecules against the Androgen receptor target [1] [2].
Tasks
1
Task type
regression
Total samples
659
Recommended split
activity_cliff
Recommended metric
RMSE
- 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.
force_update (bool, default=False) – If True, always re-download the dataset from HuggingFace Hub, even if it is already present locally. If False, the dataset is downloaded only if it is not yet available locally.
- 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
Examples
>>> from skfp.datasets.moleculeace import load_chembl1871_ki >>> dataset = load_chembl1871_ki() >>> dataset (['CC1=CC(C)(C)Nc2ccc3c(c21)/C(=C/c1ccsc1)Oc1ccc(F)cc1-3, ..., 'CN(C[C@](C)(O)C(=O)Nc1ccc(C#N)c(C(F)(F)F)c1)c1ccc(C#N)c(-c2ccccc2)c1'], \ array([-2.825, ..., -1.892]))
>>> dataset = load_chembl1871_ki(as_frame=True) >>> dataset.head() SMILES Ki 0 CC1=CC(C)(C)Nc2ccc3c(c21)/C(=C/c1ccsc1)Oc1ccc(... -2.825426 1 CCc1ccccc1/C=C1\Oc2ccc(F)cc2-c2ccc3c(c21)C(C)=... -3.201124 2 CC1=CC(C)(C)Nc2ccc3c(c21)/C(=C/c1ccccc1N(C)C)O... -2.913284 3 CC1=CC(C)(C)Nc2ccc3c(c21)/C(=C/c1ccccc1)Oc1c(F... -3.163161 4 CC(=O)O[C@]1(C(C)=O)CC[C@H]2[C@@H]3C[C@H](C)C4... -0.462398