ML package
Project description
ML Package
A Package through which multiple things can be done in a go like fitting a model of your own choice (regression/classification) and get final results in terms of model accuracy/ score/ mse/ mae/ confusion matrix and direct submission file which we need to upload in case of competitions.
Two things can be achieved from this package:
- Results after fitting any Regression/classification algorithm of your own choice. Function to be used - train_model
- Final submission file to be submitted directly in competitions. Function to be used - return_csv
Requirements:
- sklearn
- numpy
- pandas
- Pre-processed data to be passed - data already cleaned, splitted into train and test
- In train_model function, parameters to be passed:
- x_train, y_train, x_test, y_test
- model object
- regression=True (if addressing regression problem)
- regression=False (if addressing classification problem (default is True))
- In return_csv function, parameters to be passed:
- x_train, y_train, x_test, y_test
- model object
- sample submission file (dataframe)
- target column name (string)
- file location name (filepath where to be saved)
Installation & Usage
- Make sure that your pip version is up-to-date: pip install --upgrade pip. Check version with pip -V.
- Select the correct package:
- There are two packages (two versions of the package )and you should SELECT ONLY ONE OF THEM which is the latest one.
- Install using
pip install mlpkg
with latest version
- Import the package and use its functions:
from ML_Utility import ML_package
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mlpkg-0.3.tar.gz
(2.8 kB
view hashes)
Built Distribution
mlpkg-0.3-py3-none-any.whl
(3.9 kB
view hashes)