A Python package to get toposis rankings for any table.
UCS633 Project Submission
- Name - Kartikey Tiwari
- Roll no. - 101703282
kt-toposis is a Python package for displaying ranking of all criteria using Topsis technique to get good computational efficiency and ability to measure the relative performance for each alternative in a simple mathematical form.
Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is one of the multi-criteria models in making decision which is known for its simplicity, rationality, comprehensibility and good computational efficiency. Multi-criteria decision making (MCDM) refers to making choice of the best alternative from among a finite set of decision alternatives in terms of multiple, usually conflicting criteria.
These instructions will help you to install and use this package for general use.
Your csv file should not have categorical data
Use the package manager pip to install foobar.
pip install kt-toposis
You can import it either in Python IDLE or run directly through command prompt
For Command Prompt
If you want to use this package on "data.csv" file with 4 columns. You need to change the directory where "data.csv" is stored then. Here -w represents weights which signifies weight of each feature or column in our dataset and -i represents impacts which signifies impact of each column or feature in our data. If a feature is good we will use + to denote else we will use -
kt-toposis data.csv -w 1 1 1 1 -i + + - +
You can use the following command for help
For Python IDLE
from kt_toposis.topsis import top top(X,weights,impacts) #X should be a matrix #impacts should be a list of string + for positive impact - for negative impact #weights should be a list of int or float
kt-toposis Book1.csv -w 1 1 1 1 1 -i + + + + +
Topsis Selection Models | Rank ----------------------- 1 | 3 2 | 5 3 | 4 4 | 1 5 | 2 Successfully executed
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
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