A Python package implementing TOPSIS for MCDM
Project description
Ekaspreet-topsis-102017078
Topsis in Python
Author: Ekaspreet 102017078
Maintainer: Ekaspreet ekaspreet0209@gmail.com.
TOPSIS: It is a for Multiple Criteria Decision Making,A Technique for Order Preference by Similarity to Ideal
More details at wikipedia.
In Command Prompt
>> topsis data.csv "1,1,1,1" "+,+,-,+" result.csv
Input file (data.csv)
Model | Correlation | R2 | RMSE | Accuracy |
---|---|---|---|---|
M1 | 0.79 | 0.62 | 1.25 | 60.89 |
M2 | 0.66 | 0.44 | 2.89 | 63.07 |
M3 | 0.56 | 0.31 | 1.57 | 62.87 |
M4 | 0.82 | 0.67 | 2.68 | 70.19 |
M5 | 0.75 | 0.56 | 1.3 | 80.39 |
Weights (weights
) is not already normalised will be normalised later in the code.
Information of positive(+) or negative(-) impact criteria should be provided in impacts
.
Output file (result.csv)
Model | Correlation | R2 | RMSE | Accuracy | Score | Rank |
---|---|---|---|---|---|---|
M1 | 0.79 | 0.62 | 1.25 | 60.89 | 0.7722 | 2 |
M2 | 0.66 | 0.44 | 2.89 | 63.07 | 0.2255 | 5 |
M3 | 0.56 | 0.31 | 1.57 | 62.87 | 0.4388 | 4 |
M4 | 0.82 | 0.67 | 2.68 | 70.19 | 0.5238 | 3 |
M5 | 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 **Score** and **Rank**
Project details
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
Close
Hashes for Ekaspreet-topsis-102017078-1.0.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | b24815cec11f7862f367db4f4746916bbec680a49c24ce33e0425e04224f0379 |
|
MD5 | 8b1d880cedb33e88c34fd3f448feb1dd |
|
BLAKE2b-256 | 2d2e2d9d85fc630e7fd384321e3bdb695262c532aeabb67d948b58bdbdb8cb6a |
Close
Hashes for Ekaspreet_topsis_102017078-1.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3583030b61cdba8d37db6f4f18e2f0ce7edb4bd79f72d41f14155702e5e23587 |
|
MD5 | 8006019f6a9e2e84d59755aad38223ae |
|
BLAKE2b-256 | 53d02c78d83fe7a399cd0d4a76f5467ff3740acd967aa541ac0eb308d53d132d |