Fruit Classification using PCA and Various Classifiers

[Varunshiyam]

Is your feature request related to a problem? Please describe.

The project aims to address the challenges associated with high-dimensional data in image classification, such as:

• High Computational Cost: Processing large image datasets can be computationally intensive.
• Feature Redundancy: High-dimensional data often includes redundant features that do not contribute to model accuracy.
• Model Overfitting: Increased complexity can lead to overfitting, where the model performs well on training data but poorly on unseen data.

Describe the solution you'd like

This project is centered around the classification of different types of fruit images using Principal Component Analysis (PCA) for dimensionality reduction and applying various machine learning algorithms for classification, such as:

• Support Vector Machine (SVM)
• k-Nearest Neighbors (KNN)
• Decision Tree Classifier

[github-actions]

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[github-actions]

Hello @Varunshiyam! Your issue #872 has been closed. Thank you for your contribution!