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topsis marking for dataset to be ranked according to topsis analysis

Project description

TOPSIS Package in Python

Submitted by: Karanbir singh

Roll no: 101803235

Data science


Concept of TOPSIS

TOPSIS is an acronym that stands for ‘Technique of Order Preference Similarity to the Ideal Solution’ and is a pretty straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solution and comparing the distance of each one of the alternatives to those.


How to use

The package TOPSIS-Karanbir-101803235 can be run though the command line as follows:

>> pip install TOPSIS-Karanbir-101803235==0.1
>> python
>>>from topsis_analysis.topsispackage import topsis
>>>topsis("data.csv","1,1,1,2","+,+,-,+","output.csv")

Note:

  • Usages:

    topsis( <InputDataFile> <Weights> <Impacts> <ResultFileName>)

  • Input File:

    • Input file contain three or more columns.
    • First column is the object/variable name (e.g. M1, M2, M3, M4……) .
    • From 2nd to last columns contain numeric values only.
  • Output File:

    • Result file contains all the columns of input file and two additional columns having TOPSIS SCORE and RANK
  • The output is created in the form of csv file and stored and also it is displayed.

  • The impacts given in the command line should be either ‘+’ or ‘–’ depending if you want to maximise the column parameter or minimise it.

Sample Input

Here is a sample set of data which can be used for the following package:

ModelCorrelationR2RMSEAccuracy
M10.790.621.2560.89
M20.660.442.8963.07
M30.560.311.5762.87
M40.820.672.6870.19
M50.750.561.380.39

Output of this sample input

The output that will be generated from the following input data will be:

ModelCorrelationR2RMSEAccuracyTopsis ScoreRank
M10.790.621.2560.890.63913301413425902.0
M20.660.442.8963.070.212591829692779005.0
M30.560.311.5762.870.40784567761305204.0
M40.820.672.6870.190.51915323950074703.0
M50.750.561.380.390.82826658519358101.0

Here the ranks are given as rank 1 is the best solution according to the weights and impacts given and rank 5 is the worst solution.


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