| Name | Topsis-Pranav-102003432 JSON |
| Version |
0.13
JSON |
| download |
| home_page | |
| Summary | This is a topsis package of version 0.13 |
| upload_time | 2023-01-22 21:42:32 |
| maintainer | |
| docs_url | None |
| author | Pranav Singh |
| requires_python | |
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## Topsis_Pranav_102003432
# TOPSIS
Submitted By: **Pranav Singh - 102003432**.
Type: **Package**.
Title: **TOPSIS method for multiple-criteria decision making (MCDM)**.
Version: **1.0.0**.
Date: **2022-01-22**.
Author: **Pranav Singh**.
Maintainer: **Pranav Singh <psingh2_be20@thapar.edu>**.
Description: **Evaluation of alternatives based on multiple criteria using TOPSIS method.**.
---
## What is TOPSIS?
**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution
(TOPSIS) originated in the 1980s as a multi-criteria decision making method.
TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution,
and greatest distance from the negative-ideal solution.
<br>
## How to install this package:
```
>> pip install Topsis-Pranav-102003432
```
### In Command Prompt
```
>> topsis data.csv "1,1,1,1,1" "+,+,-,+,-" result.csv
```
## Input file (data.csv)
The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R<sup>2</sup>, Root Mean Squared Error, Correlation, and many more.
| Model | P1 | P2 | P3 | P4 | P5 |
| ----- | ----------- | ------------- | ---- | -------- | ---- |
| M1 | 0.7 | 0.5 | 7 | 37 | 11.3 |
| M2 | 0.8 | 0.6 | 7 | 46 | 13.4 |
| M3 | 0.7 | 0.5 | 7 | 48 | 14 |
| M4 | 0.9 | 0.8 | 7 | 44 | 13.2 |
| M5 | 0.9 | 0.9 | 5 | 37 | 11.1 |
| M6 | 0.9 | 0.6 | 3 | 67 | 18 |
| M7 | 0.9 | 0.5 | 7 | 39 | 11.8 |
| M8 | 0.9 | 0.9 | 5 | 46 | 13.2 |
Weights (`weights`) is not already normalised will be normalised later in the code.
Information of benefit positive(+) or negative(-) impact criteria should be provided in `impacts`.
<br>
## Output file (result.csv)
| Model | P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank |
| ----- | ----------- | ------------- | ---- | -------- | ---- |-----| ----|
| M1 | 0.7 | 0.5 | 7 | 37 | 11.3 | 0.28016 | 5 |
| M2 | 0.8 | 0.6 | 7 | 46 | 13.4 | 0.8292 | 1 |
| M3 | 0.7 | 0.5 | 7 | 48 | 14 | 0.17536 | 8 |
| M4 | 0.9 | 0.8 | 7 | 44 | 13.2 | 0.25 | 7 |
| M5 | 0.9 | 0.9 | 5 | 37 | 11.1 | 0.56483 | 3 |
| M6 | 0.9 | 0.6 | 3 | 67 | 18 | 0.27313 | 6 |
| M7 | 0.9 | 0.5 | 7 | 39 | 11.8 | 0.55075 | 4 |
| M8 | 0.9 | 0.9 | 5 | 46 | 13.2 | 0.65029 | 2 |
<br>
The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**
Raw data
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