load_freesolv#
- skfp.datasets.moleculenet.load_freesolv(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) DataFrame | tuple[list[str]] | ndarray#
Load and return the FreeSolv (Free Solvation Database) dataset.
The task is to predict hydration free energy of small molecules in water [1] [2]. Targets are in kcal/mol.
Tasks
1
Task type
regression
Total samples
642
Recommended split
scaffold
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 float 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
Examples
>>> from skfp.datasets.moleculenet import load_freesolv >>> dataset = load_freesolv() >>> dataset (['CN(C)C(=O)c1ccc(cc1)OC', ..., 'C1COCCO1'], array([-1.101e+01, -4.870e+00, ..., 2.900e-01, -5.060e+00]))
>>> dataset = load_freesolv(as_frame=True) >>> dataset.head() SMILES label 0 CN(C)C(=O)c1ccc(cc1)OC -11.01 1 CS(=O)(=O)Cl -4.87 2 CC(C)C=C 1.83 3 CCc1cnccn1 -5.45 4 CCCCCCCO -4.21