# TOPSIS-Python
Submitted By: **Girik Garg 102003178**
***
## 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. More details at [wikipedia](https://en.wikipedia.org/wiki/TOPSIS).
<br>
## How to use this package:
TOPSIS-GIRIK-GARG-102003178 can be run as in the following example:
### In Command Prompt to run the code:
```
topsis data.csv "1,1,1,1" "+,+,-,+" out.csv
```
<br>
## Sample dataset
The decision matrix (`a`) should be constructed with each row representing a Model alternative, and each column representing a criterion like Fund Name , P1 ,P2 , P3 , P4 , P5.
Model | Correlation | R<sup>2</sup> | RMSE | Accuracy
------------ | ------------- | ------------ | ------------- | ------------
M1| 0.8 |0.64 |3.5 |37.5 |10.61
M2| 0.86 |0.74 |3.4 |42.2 |11.8
M3| 0.69 |0.48 |5.7 |70 |19.22
M4| 0.65 |0.42 |5.7 |65.5 |18.07
M5| 0.9 |0.81 |6.6 |39.1 |11.85
M6| 0.76 |0.58 |4 |53.5 |14.71
M7| 0.69 |0.48 |6.2 |51.3 |14.67
M8| 0.65 |0.42 |6 |50.2 |14.32
<br>
## Output
```
Row_NO Performance_score Rank
1 0.436737 7
2 0.389937 8
3 0.565650 4
4 0.590487 3
5 0.522924 5
6 0.451344 6
7 0.637889 1
8 0.635536 2
```
<br>
The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.
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"description": "# TOPSIS-Python\r\n\r\nSubmitted By: **Girik Garg 102003178**\r\n\r\n***\r\n\r\n## What is TOPSIS\r\n\r\n**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal\r\n**S**olution (TOPSIS) originated in the 1980s as a multi-criteria decision\r\nmaking method. TOPSIS chooses the alternative of shortest Euclidean distance\r\nfrom the ideal solution, and greatest distance from the negative-ideal\r\nsolution. More details at [wikipedia](https://en.wikipedia.org/wiki/TOPSIS).\r\n\r\n<br>\r\n\r\n## How to use this package:\r\n\r\nTOPSIS-GIRIK-GARG-102003178 can be run as in the following example:\r\n\r\n\r\n### In Command Prompt to run the code:\r\n```\r\ntopsis data.csv \"1,1,1,1\" \"+,+,-,+\" out.csv\r\n```\r\n<br>\r\n\r\n## Sample dataset\r\n\r\nThe decision matrix (`a`) should be constructed with each row representing a Model alternative, and each column representing a criterion like Fund Name , P1 ,P2 , P3 , P4 , P5.\r\n\r\nModel | Correlation | R<sup>2</sup> | RMSE | Accuracy\r\n------------ | ------------- | ------------ | ------------- | ------------\r\nM1|\t0.8\t|0.64\t|3.5\t|37.5\t|10.61\r\nM2|\t0.86\t|0.74\t|3.4\t|42.2\t|11.8\r\nM3|\t0.69\t|0.48\t|5.7\t|70\t|19.22\r\nM4|\t0.65\t|0.42\t|5.7\t|65.5\t|18.07\r\nM5|\t0.9\t|0.81\t|6.6\t|39.1\t|11.85\r\nM6|\t0.76\t|0.58\t|4\t|53.5\t|14.71\r\nM7|\t0.69\t|0.48\t|6.2\t|51.3\t|14.67\r\nM8|\t0.65\t|0.42\t|6\t|50.2\t|14.32\r\n\r\n\r\n\r\n<br>\r\n\r\n## Output\r\n\r\n```\r\nRow_NO\tPerformance_score\tRank\r\n1\t 0.436737\t 7\r\n2\t 0.389937\t 8\r\n3\t 0.565650 4\r\n4\t 0.590487\t 3\r\n5\t 0.522924\t 5\r\n6\t 0.451344\t 6\r\n7\t 0.637889\t 1\r\n8\t 0.635536\t 2\r\n\r\n```\r\n<br>\r\nThe rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best decision, and last rank offering the worst decision making, according to TOPSIS method.\r\n",
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