Observed since 20 Oct, 15:06 UTC
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102003037-topsis
Topsis
Roll Number : 102003037
Subgroup : 3COE18
The program takes csv file containing our data to be ranked, weights and impacts in the form of "+" or "-", seperated by commas as inputs and then outputs a resultant csv file with two additional columns of performance score and Ranks.
TOPSIS, Technique of Order Preference Similarity to the Ideal Solution, is a multi-criteria decision analysis method (MCDA).
It chooses the alternative of shortest the Euclidean distance from the ideal solution and greatest distance from the negative ideal solution.
using pip install:-
pip install 102003037-topsis-Himangi
Open terminal and type
102003037 102003037-data.csv "1,1,1,1" "+,+,-,+" 102003037-output.csv
The output will then be saved in a newly created CSV file whose name will be provided in the command line by the user.
Topsis mathematical operations to be performed on the input file which contains a dataset having different fields.
The weights to assigned to the different parameters in the dataset should be passed in the argument, seperated by commas.
The impacts are passed to consider which parameters have a positive impact on the decision and which one have the negative impact. Only '+' and '-' values should be passed and should be seperated with ',' only.
This argument is used to pass the path of the result file where we want the rank and performance score to be stored.
Download counts and popularity will appear here as the collector receives them.
| Package / target | Requirement | Relationship |
|---|---|---|
numpyEnvironment{
"extras": "",
"marker": null,
"requires_python": "",
"evaluation": "NOT_EVALUATED"
} | numpy | runtime |
pandasEnvironment{
"extras": "",
"marker": null,
"requires_python": "",
"evaluation": "NOT_EVALUATED"
} | pandas | runtime |
bdist_wheel · 2.82 KB · Python py3
sdist · 2.82 KB · Python source
Observed since 20 Oct, 15:06 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
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