SklearnModel¶
-
class
mastml.models.SklearnModel(model, **kwargs)[source]¶ Bases:
sklearn.base.BaseEstimator,sklearn.base.TransformerMixinClass to wrap any sklearn estimator, and provide some new dataframe functionality
- Args:
model: (str), string denoting the name of an sklearn estimator object, e.g. KernelRidge
kwargs: keyword pairs of values to include for model, e.g. for KernelRidge can specify kernel, alpha, gamma values
- Methods:
- fit: method that fits the model parameters to the provided training data
- Args:
X: (pd.DataFrame), dataframe of X features
y: (pd.Series), series of y target data
- Returns:
- fitted model
- predict: method that evaluates model on new data to give predictions
- Args:
X: (pd.DataFrame), dataframe of X features
as_frame: (bool), whether to return data as pandas dataframe (else numpy array)
- Returns:
- series or array of predicted values
- help: method to output key information on class use, e.g. methods and parameters
- Args:
- None
- Returns:
- None, but outputs help to screen
Methods Summary
fit(X, y)get_params([deep])Get parameters for this estimator. help()predict(X[, as_frame])Methods Documentation