semvec/pypi-packages huggingface dataset:
Topsis-Pooja-102303845 1.0.1
TOPSIS implementation using Python

# TOPSIS – Python Package

**By:** Pooja\
**Roll Number:** 102303845\
**Course:** UCS654 – Predictive Analytics using Statistics

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## Project Description

**TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)** is a multi-criteria decision-making (MCDM) method used to rank alternatives based on their distance from an ideal best solution and an ideal worst solution.

This Python package provides an easy-to-use **command-line implementation** of the TOPSIS algorithm. Users can input a dataset along with weights and impacts and obtain ranked results based on TOPSIS scores.

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## Installation

Install the package using pip:

```bash
pip install Topsis-Pooja-102303845
```

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## Usage

Run the following command:

```
topsis <inputFile> <weights> <impacts> <outputFile>
```

Example:

```
topsis sample.csv "1,1,1,1" "+,+,-,+" result.csv
```

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## Input File Format

- The input file must contain at least three columns
- The first column should contain alternative names
- All other columns must contain numeric values only
- The number of weights and impacts must match the number of criteria

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## Sample Input File

| Model | Storage | Camera | Price | Looks |
| ----- | ------- | ------ | ----- | ----- |
| M1    | 16      | 12     | 250   | 5     |
| M2    | 16      | 8      | 200   | 3     |
| M3    | 32      | 16     | 300   | 4     |
| M4    | 32      | 8      | 275   | 4     |
| M5    | 16      | 16     | 225   | 2     |

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## Output

The output file contains:

- Topsis Score
- Rank

The alternative with Rank 1 is considered the best choice.

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## Conclusion

This package simplifies the application of the TOPSIS method and enables efficient decision-making using multiple criteria through a simple command-line interface.