Metadata-Version: 2.1
Name: submission
Version: 0.0.2
Summary: Takes algorithm, train, test, X variables, Y variables, column names required for submission and name of submission file as input and produces an output csv for submitting in the competition.
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Platform: UNKNOWN

# 'Submission' Package for various online competitions.

This package helps the user to make submission file in '.csv' format (viz the criterion for most competitions) in a simple way.

Installation:

Run the following to install,
#Python
pip install submission

How it works?

It takes the algorithm, training dataset, test dataset, X variables, Y variables, column names (particular columns required for submission) and name of submission file (desired by the user) as input and produces an outputs the accuracy , RMSE and Cross-Validation score of that model and in .csv for submitting in the competition.

How to use:

from sklearn.tree import DecisionTreeRegressor
DT = DecisionTreeRegressor(max_depth=15, min_samples_leaf=100)
submission.modelfit(DT, train_df, test_df, predictors, target, IDcol, 'DT.csv')

Output:
Model Report
Accuracy : 84%
RMSE : 2914
CV Score : Mean - 2941 | Std - 20.86 | Min - 2907 | Max - 2975

