Ekaspreet-topsis-102017078
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.
>> topsis data.csv "1,1,1,1" "+,+,-,+" result.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
.
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**