metbit.lazy_opls_da

Analysis and models module in metbit 4.0.1.

import metbit.lazy_opls_da

Classes

lazy_opls_da

Methods

__init__(self, data: pd.DataFrame, groups: list, working_dir: str, n_components: int=2, scaling: str='pareto', estimator: str='opls', kfold: int=3, random_state: int=94, auto_ncomp: bool=True, permutation: bool=True, VIP: bool=True, linear_regression: bool=True)

This function takes in a dataframe and a list of y values and returns the project_name model.

Parameters

datapandas dataframe

The dataframe to be used.

ylist

The list of y values.

n_componentsint

The number of components to use. lazy_opls_da(data, y, n_components).fit()

fit(self, marker_color: dict=None)

Source

metbit/lazy_opls_da.py at v4.0.1