kalayil

This project is a python module for making machine learning workflow easier than ever before.

Installation

Run the following to install:

'''python pip install kalayil '''

'''python

from kalayil import modelling as kl

Rull All Machine Learning Classificatin alogorithms at once and see the results

RunAll(models,data,phase='',scores=None,trained_models = {},use_params=False)

Feature Scale your data OHE_features refers to one hot encoded features. OHE_features are to be listed to avoid them

FeatureScale(data,OHE_features,scaler='MinMaxScaler')

'''

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

kalayil-0.1.4.tar.gz (11.9 kB view details)

Uploaded Jan 15, 2020 Source

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

kalayil-0.1.4-py3-none-any.whl (8.2 kB view details)

Uploaded Jan 15, 2020 Python 3

Details for the file kalayil-0.1.4.tar.gz.

Download URL: kalayil-0.1.4.tar.gz
Upload date: Jan 15, 2020
Size: 11.9 kB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.3

Hashes for kalayil-0.1.4.tar.gz
Algorithm	Hash digest
SHA256	`44e06774dd2dbd6b22a85e263046fe1a06e5a1780e09d681867231fdf1aa81fa`
MD5	`8881b208719ca093b26978f5562f1699`
BLAKE2b-256	`d39acb8eba3479b1184cb5eddc42097b8fcce610e3237459ebb7dac4b74c192f`

Details for the file kalayil-0.1.4-py3-none-any.whl.

Download URL: kalayil-0.1.4-py3-none-any.whl
Upload date: Jan 15, 2020
Size: 8.2 kB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.3

Hashes for kalayil-0.1.4-py3-none-any.whl
Algorithm	Hash digest
SHA256	`1444160a0ffa736bb6a9fd9352013826e12242090de81c2e78f2dd98039ebff5`
MD5	`83c98965ad9b58730d347d286f4e3dcd`
BLAKE2b-256	`f6485feb3bfb4f6d932cc64b35dc4de72f7ed9736c0745da035b5e137dc871c4`