# ‘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 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, X, Y, IDcol, ‘DT.csv’)
Output:
Model Report
RMSE : 2914
CV Score : Mean - 2941 | Std - 20.86 | Min - 2907 | Max - 2975
3 maintainers
Metadata
3 maintainers
Release files for submission 0.0.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| submission-0.0.3.tar.gz | 1.9 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| submission-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.1 kB
Release files / submission-0.0.3.tar.gz
| Download URL | submission-0.0.3.tar.gz |
|---|---|
| Size | 1.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
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Release files / submission-0.0.3-py3-none-any.whl
| Download URL | submission-0.0.3-py3-none-any.whl |
|---|---|
| Size | 2.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
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Security for submission 0.0.3
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