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A python package for implementing Markov Chain Type 4 rank aggregation

Project description

Markov Chain Type 4 Rank Aggregation

** implementation of MC4 Rank Aggregation algorithm using Python**


This project is all about implementing one of the most popular rank aggregation algorithms Markov Chain Type 4 or MC4. In the field of Machine Learning and many other scientific problems, several items are often needed to be ranked based on some criterion. However, different ranking schemes order the items based on different preference criteria. Hence the rankings produced by them may differ greatly.

Therefore a rank aggregation technique is often used for combining the individual rank lists into a single aggregated ranking. Though there are many rank aggregation algorithms, MC4 is one of the most renowned ones.


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For the latest release, pip install mc4

For a specific release,pip install mc4=={version} such as pip install mc4==1.0


Please Note: As per the latest release(v1.0), This package works with CSV files only. We will add more features, controls and file support in the upcoming releases.

Using this package is very easy. You just need the following three lines of code to use the package.

from mc4.algorithm import mc4_aggregator

aggregated_ranks = mc4_aggregator('dataset.csv')


here dataset.csv is a dataset containing ranks provided by different ranking algorithms or rank lists. You can refer here for more info and some test datasets.

MC4_Aggregator takes some additional arguments as well.

  • header_row (int or None): row number of the dataset containing the header, default is 0
  • index_col (int or None): column number of the dataset containing the index, default is 0
  • precision (float): acceptable error margin for convergence, default is 1e-07
  • iterations (int): number of iterations to reach stationary distribution, default is 200
  • erg_number (float): small, positive number used to calculate ergodic transition matrix, default is 0.15


Upcoming features

  • Column major support
  • Pandas dataframe as a dataset support

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