Make CalculatorPipeliner

[lodurality]

Make CalculatorPipeliner which doesn't use eval_cv and grid_cv and predictive_models. You need only to specify data transforming steps and list of calculating functions (instead of scoring functions) to calculate on data. Example: ICC calculations for MICCAI.

Example:

feature_engineering = [('VT', VarianceThreshold()),
                       ('PCA', PCA())]

# Preprocessing step variants (2nd step)
scalers = [('standard', StandardScaler()),
           ('minmax', MinMaxScaler())]

# Reskit needs to define steps in this manner
steps = [('feature_engineering', feature_engineering),
         ('scaler', scalers)]
calc_pipe = CalculatorPipeliner(steps)

calculators = {'ICC' : ICC_func,
                       'MAX', Max_func}
calc_pipe.get_results(X, y = None, calculators = calculators)