https://github.com/abhinav330/iris-dataset-classic-ml-problem

This repository demonstrates the classification of Iris flowers into three species (Setosa, Versicolor, Virginica) using a Support Vector Machine (SVM) classifier.
https://github.com/abhinav330/iris-dataset-classic-ml-problem

classification data-science iris-dataset jupyter machine-learning numpy pandas python sklearn support-vector-machines svm-classifier

Last synced: 19 days ago
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This repository demonstrates the classification of Iris flowers into three species (Setosa, Versicolor, Virginica) using a Support Vector Machine (SVM) classifier.

• Host: GitHub
• URL: https://github.com/abhinav330/iris-dataset-classic-ml-problem
• Owner: Abhinav330
• Created: 2024-08-25T23:16:35.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-31T02:58:43.000Z (almost 2 years ago)
• Last Synced: 2025-03-03T08:16:35.045Z (over 1 year ago)
• Topics: classification, data-science, iris-dataset, jupyter, machine-learning, numpy, pandas, python, sklearn, support-vector-machines, svm-classifier
• Language: Jupyter Notebook
• Homepage:
• Size: 4.04 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Support: Support Vector Machines Project.ipynb

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# Irish-dataset-classic-ml-problem

This repository demonstrates the classification of Iris flowers into three species (Setosa, Versicolor, Virginica) using a Support Vector Machine (SVM) classifier.

1. **Data Preparation:** Loads the Iris dataset and performs necessary preprocessing.

2. **Data Exploration:** Visualizes the data to understand relationships between features and species.

3. **Model Training:** Trains an SVM classifier on the training data.

4. **Model Evaluation:** Evaluates the model's performance using metrics like confusion matrix and classification report.

5. **Hyperparameter Tuning:** Optimizes the SVM model using GridSearchCV to find the best hyperparameters.