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๐Ÿ“Š Predicting stock price direction using Support Vector Machine (SVM), with a focus on both theoretical foundations and practical implementation. Includes evaluation via confusion matrix, classification report, and heatmap visualization.

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Marouf-Haider/Support-Vector-Machine

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Support Vector Machine Classifier

This project implements a Support Vector Machine (SVM) classifier using Scikit-learn. The goal is to train and evaluate a model on a classification dataset.

Features

  • Train/test split
  • SVM model with configurable kernel
  • Confusion matrix and classification report
  • Heatmap visualization

Requirements

Install dependencies:

pip install -r requirements.txt

Usage

Update the dataset filename and target column in svm_classifier.py, then run:

python svm_classifier.py

License

MIT

Contact

Email:

Linkedin: www.linkedin.com/in/haider-marouf-1149b1316

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๐Ÿ“Š Predicting stock price direction using Support Vector Machine (SVM), with a focus on both theoretical foundations and practical implementation. Includes evaluation via confusion matrix, classification report, and heatmap visualization.

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