This is a Python library for handling problems related to Multiple Criteria Decision Making(MCDM)
Project description
TOPSIS
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 1.0.1.
Author: Shubham Malhotra.
Description: Evaluation of alternatives based on multiple criteria using TOPSIS method.
How to install this package:
>> pip install Topsis-Shubham-102003109
In Command Prompt
>> topsis 102003109-data.csv "1,2,1,2,1" "+,+,-,-,+" resultdata.csv
Input file (data.csv)
| Model | Correlation | R^2 | RMSE | Accuracy |
|---|---|---|---|---|
| P1 | 0.79 | 0.62 | 1.25 | 60.89 |
| P2 | 0.66 | 0.44 | 2.89 | 63.07 |
| P3 | 0.56 | 0.31 | 1.57 | 62.87 |
| P4 | 0.82 | 0.67 | 2.68 | 70.19 |
| P5 | 0.75 | 0.56 | 1.3 | 80.39 |
Output file (result.csv)
| Model | Correlation | R^2 | RMSE | Accuracy | Topsis_score | Rank |
|---|---|---|---|---|---|---|
| P1 | 0.79 | 0.62 | 1.25 | 60.89 | 0.7722 | 2 |
| P2 | 0.66 | 0.44 | 2.89 | 63.07 | 0.2255 | 5 |
| P3 | 0.56 | 0.31 | 1.57 | 62.87 | 0.4388 | 4 |
| P4 | 0.82 | 0.67 | 2.68 | 70.19 | 0.5238 | 3 |
| P5 | 0.75 | 0.56 | 1.3 | 80.39 | 0.8113 | 1 |
The output file contains columns of input file along with two additional columns having Topsis_score and Rank
TOPSIS
Title: TOPSIS method for multiple-criteria decision making (MCDM).
Version: 1.0.1.
Author: Shubham Malhotra.
Description: Evaluation of alternatives based on multiple criteria using TOPSIS method.
How to install this package:
>> pip install Topsis-Shubham-102003109
In Command Prompt
>> topsis 102003109-data.csv "1,2,1,2,1" "+,+,-,-,+" resultdata.csv
Input file (data.csv)
| Model | Correlation | R^2 | RMSE | Accuracy |
|---|---|---|---|---|
| P1 | 0.79 | 0.62 | 1.25 | 60.89 |
| P2 | 0.66 | 0.44 | 2.89 | 63.07 |
| P3 | 0.56 | 0.31 | 1.57 | 62.87 |
| P4 | 0.82 | 0.67 | 2.68 | 70.19 |
| P5 | 0.75 | 0.56 | 1.3 | 80.39 |
Output file (result.csv)
| Model | Correlation | R^2 | RMSE | Accuracy | Topsis_score | Rank |
|---|---|---|---|---|---|---|
| P1 | 0.79 | 0.62 | 1.25 | 60.89 | 0.7722 | 2 |
| P2 | 0.66 | 0.44 | 2.89 | 63.07 | 0.2255 | 5 |
| P3 | 0.56 | 0.31 | 1.57 | 62.87 | 0.4388 | 4 |
| P4 | 0.82 | 0.67 | 2.68 | 70.19 | 0.5238 | 3 |
| P5 | 0.75 | 0.56 | 1.3 | 80.39 | 0.8113 | 1 |
The output file contains columns of input file along with two additional columns having Topsis_score and Rank
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file Topsis-Shubham-102003109-1.0.2.tar.gz.
File metadata
- Download URL: Topsis-Shubham-102003109-1.0.2.tar.gz
- Upload date:
- Size: 4.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d064727391abff616c0647002c307c399f871279ad18e8cba5576549501c3eb5
|
|
| MD5 |
61dbc62e195e9c5798bc4d3f3e6dbb6d
|
|
| BLAKE2b-256 |
d51fe4fd6dbd158cbbb5a7a622752dea8cbefb7d6084de10939cb5c359166d49
|
File details
Details for the file Topsis_Shubham_102003109-1.0.2-py3-none-any.whl.
File metadata
- Download URL: Topsis_Shubham_102003109-1.0.2-py3-none-any.whl
- Upload date:
- Size: 5.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
467a4f949c4061f1e1e167fa513b0b59c77391a000f9a4e7db30fe3529f5a471
|
|
| MD5 |
ea9a2c856e2747b99a9f68b36eac53ef
|
|
| BLAKE2b-256 |
c89617853c968780cc9265b43b595306ee77de853c1e505d73a755684ba7b4bf
|
