This repository contains the code for a simple classification task that aims to classify Iris flowers into different species. The model is trained on the famous Iris Species dataset, available on Kaggle.
The Iris Species dataset is available on Kaggle: Iris Species Dataset.
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Dataset Description: The dataset includes measurements of sepal length, sepal width, petal length, and petal width for three different species of iris flowers: setosa, versicolor, and virginica.
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Dataset Structure:
iris.csv: CSV file containing the measurements and corresponding labels.
The classification model is implemented. It uses a simple machine learning algorithm to classify iris species based on the provided measurements. Accuracy of 97% was acheived.
Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or create a pull request.