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A Python package to evaluate ranks of a Multiple Criteria Decision Making Problem(MCDM) using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)

Project description

Project UCS633

Name Kriti Pandey

Roll no 101703292

Group 3COE13

Installation

Use the package manager pip to install TOPSIS-ANALYSIS-kriti.

pip install TOPSIS-ANALYSIS-kriti

Usage

Enter csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-)

TOPO_101703292 data.csv [1,1,1,1] [+,+,-,+]

Sample dataset

ID EYES NOSE FOREHEAD LIPS CHIN
S1 0.79 0.62 1.25 60.89 11
S2 0.66 0.44 2.89 63.07 20
S3 0.56 0.31 1.57 62.87 16
S4 0.82 0.67 2.68 70.19 16
S5 0.75 0.56 1.3 80.39 20

Result

weights vector=[1.0, 1.0, 1.0, 1.0, 1.0]

impacts vector=['+', '-', '+', '+', '+']

Topsis Selection of DATA

Model | Rank
_______________

1     | 5

2     | 1

3     | 3

4     | 2

5     | 4
_______________

Constraint

Your csv file should not have categorical data

License

MIT

Project details


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TOPSIS_ANALYSIS_kriti-1.0.6.tar.gz (3.3 kB view hashes)

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