Division of functions to modularize

[jbarns14]

Respond here with your plan for a function to modularize.

[meretelutz]

I'm going to work on writing a function that takes in a list of models and conducts cross-validation, returning fit time, score time, training score, and test score. It will be adapted from Varada's mean_std_cross_val_scores() function found here: https://pages.github.ubc.ca/MDS-2023-24/DSCI_571_sup-learn-1_students/lectures/02_ml-fundamentals.html?highlight=mean_std_cross_val_scores

I've opened up a branch called cross-validation-function and will be working on it there

[jbarns14]

I'm going to modularize a function to create the preprocessor given the lists of types of features (numeric, passthrough, categorical, etc).

I opened a branch called preprocessor_function and will be working on it there.

[WaleedMahmood1]

Sounds good everyone! I am going to work on modularizing a function to do the EDA (at least the graphing), using altair. I am going to open up a branch called eda_function and work on this there.

[WaleedMahmood1]

Format to follow for the docstring:

def plot_numeric_distributions(data, target, numeric_features=None): """ Plot histograms for all numeric features in the dataset.

Parameters:
- data (DataFrame): the dataset
- target (str): name of the target variable
- numeric_features (list, optional): list of names of the numeric features.
"""

[meretelutz]

All functions are passing their tests and all branches have been merged so I am closing this issue! 🤩