Pistachio-Species-Classification

Implementation of classification algorithms and K-mean clustering to classify pistachio species.

This project constitutes the second part of my assignment for The Machine Learning & Deep Learning Show 2022

📌Link to the assignment

Open with drive

🏷️Tech Stack Used

Python3, NumPy, Pandas and Matplotlib libraries

Problem Statement

• Find data and implement classification algorithms (more algorithms you try, the better).
• Remove ‘Y’ column form your classification data, and implement k-mean clustering algorithm on any two columns of the data. Make sure you plot the points before and after clustering.

Dataset

Pistachio Dataset; 2 Class - Kirmizi and Siirt Pistachio, 16 and 28 Features

Link to the source of the dataset

Code

Part 1

I’ve used a dataset that contains different features of 2 different species of pistachios for the classification model. The different classification algorithms used:

• Logistic Regression
• Naive Bayes Classification
• Decision Trees
• Random Forest
• Linear Support Vector Machine

Run Pistachio.ipynb script.

Part 2

I've used two columns "perimeter " and "roundness" to implement the k means clustering algorithm. Run Pistachio_Clustering.ipynb script.

Contributing

Contributions are always welcome! See contributing.md for ways to get started.

Please adhere to this project's code of conduct.

Authors

• @manisha-nair28

Acknowledgements

• Pistachio Dataset

License

This project is licensed under the MIT License. See the LICENSE file for more information.

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