Usage examples

Quickstart

Creating WMSDTransformer object

In order to create a WMSDTransformer object, you need to provide an aggregation function’s name. You can choose between R, standing from Relative, I (Ideal) and A (Anti-ideal).

from WMSDTransformer import WMSDTransformer
wmsd_transformer = WMSDTransformer(agg_fn = "R")

Fitting and transforming data

This is how you fit and transform data provided in form of pandas dataframe, using the fit_transform() method.

wmsd_transformer.fit_transform(your_dataframe)

Showing TOPSIS ranking

After fitting and transforming data, you can run show_ranking() method to show a TOPSIS ranking.

wmsd_transformer.show_ranking()

Showing TOPSIS results in WMSD space

To print a plot visualizing TOPSIS results in WMSD Space, you need to run plot() method.

wmsd_transformer.plot()

Notebooks

Below you will find notebooks which are prepared to show how to use the WMSDTransformer library on different types of data sets.

Students example

Data set showed in students example notebook contains only 3 criteria, each of them is gain type and ech of them has weight equal 1.

Bus example

Data set showed in bus example notebook contains 4 gain type criteria and 4 cost type criteria. Each of them has weight equal 1.

Economic index example

Data set showed in economic index example notebook contains 4 gain type criteria with different weights.