plot_pipeline_parameters

Pipeline parameter analysis plotting module for ML results analysis. Focuses on visualizing the impact of data transformations and pipeline settings on model performance.

Classes

PipelineParameterPlotter

Initializes the PipelineParameterPlotter.

Module Contents

class plot_pipeline_parameters.PipelineParameterPlotter(data: pandas.DataFrame)

Initializes the PipelineParameterPlotter.

Parameters:

data (pd.DataFrame) – Results DataFrame, must contain columns for pipeline parameters and performance metrics.

Raises:

ValueError – If no pipeline parameter columns are found in the data.

data

clean_data

categorical_params = ['resample', 'scale', 'param_space_size', 'percent_missing']

continuous_params

available_categorical

available_continuous

plot_categorical_parameters(metric: str = 'auc', figsize: Tuple[int, int] | None = None) → None

Creates box plots for categorical pipeline parameters.

Parameters:

• metric (str, optional) – The performance metric to plot. Defaults to ‘auc’.

• figsize (Optional[Tuple[int, int]], optional) – Figure size for the plot. Defaults to None.

Raises:

ValueError – If the specified metric is not found in the data.

plot_continuous_parameters(metric: str = 'auc', figsize: Tuple[int, int] | None = None) → None

Creates scatter plots for continuous pipeline parameters.

Parameters:

• metric (str, optional) – The performance metric to plot. Defaults to ‘auc’.

• figsize (Optional[Tuple[int, int]], optional) – Figure size for the plot. Defaults to None.

Raises:

ValueError – If the specified metric is not found in the data.