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A machine learning package for testing integer imputation into arrays and checking out changes in the cost. Looking for ways to extend this to dataframes as it has great potential

Project description

ARRIMPUTER 1.3.0

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What is it?

A machine learning algorithm/package for integer imputation into arrays. Integers are imputed and the cost difference is calculated to determine which integer yields the optimum cost reduction.

The package is designed for experimental purposes as there are possibilities of its application on data frames and other important projects that might need such a feature.

Installation

pip install arrimputer

Examples

Base Use

from ArrImputer import *
test_arr = [0,1,2,3,4,5]
get_optimum_integer(test_arr)

Advanced Use

from ArrImputer import *
test_arr = [0,1,2,3,4,5]
get_optimum_integer(test_arr,max_tries=1000)

Code of Conduct

Everyone interacting in the project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the PyPA Code of Conduct.

Reporting issues

Report issues to me at awesome.tingwei@outlook.com.

Project details


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arrimputer-1.3.0.tar.gz (5.2 kB view hashes)

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arrimputer-1.3.0-py3-none-any.whl (6.8 kB view hashes)

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