autoprognosis.plugins.preprocessors.feature_scaling.plugin_nop module

class NopPlugin(random_state: int = 0)

Bases: PreprocessorPlugin

Preprocessing plugin that doesn’t alter the dataset.

change_output(output: str) None
static components_interval(*args: Any, **kwargs: Any) Tuple[int, int]
fit(X: DataFrame, *args: Any, **kwargs: Any) Plugin

Train the plugin

Parameters:

X – pd.DataFrame

fit_predict(X: DataFrame, *args: Any, **kwargs: Any) DataFrame

Fit the model and predict the training data. Used by predictors.

fit_transform(X: DataFrame, *args: Any, **kwargs: Any) DataFrame

Fit the model and transform the training data. Used by imputers and preprocessors.

classmethod fqdn() str

The fully-qualified name of the plugin: type->subtype->name

static hyperparameter_space(*args: Any, **kwargs: Any) List[Params]

The hyperparameter search domain, used for tuning.

classmethod hyperparameter_space_fqdn(*args: Any, **kwargs: Any) List[Params]

The hyperparameter domain using they fully-qualified name.

is_fitted() bool

Check if the model was trained

classmethod load(buff: bytes) NopPlugin

Load the plugin from bytes

static name() str

The name of the plugin, e.g.: xgboost

predict(X: DataFrame, *args: Any, **kwargs: Any) DataFrame

Run predictions for the input. Used by predictors.

Parameters:

X – pd.DataFrame

classmethod sample_hyperparameters(trial: optuna.trial.Trial, *args: Any, **kwargs: Any) Dict[str, Any]

Sample hyperparameters for Optuna.

classmethod sample_hyperparameters_fqdn(trial: optuna.trial.Trial, *args: Any, **kwargs: Any) Dict[str, Any]

Sample hyperparameters using they fully-qualified name.

classmethod sample_hyperparameters_np(random_state: int = 0, *args: Any, **kwargs: Any) Dict[str, Any]

Sample hyperparameters as a dict.

save() bytes

Save the plugin to bytes

static subtype() str

The type of the plugin, e.g.: classifier

transform(X: DataFrame) DataFrame

Transform the input. Used by imputers and preprocessors.

Parameters:

X – pd.DataFrame

static type() str

The type of the plugin, e.g.: prediction

plugin

alias of NopPlugin