{"id":22868474,"url":"https://github.com/robcyberlab/machine-learning-classifier","last_synced_at":"2025-03-31T10:50:53.424Z","repository":{"id":263192513,"uuid":"889635399","full_name":"RobCyberLab/Machine-Learning-Classifier","owner":"RobCyberLab","description":"🤖Machine Learning Classifier⚙️","archived":false,"fork":false,"pushed_at":"2024-11-16T21:26:33.000Z","size":255,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-06T15:53:31.300Z","etag":null,"topics":["ai","artificial-intelligence","classifiers","data-analysis","data-science","deep-learning","digit-recognition","machine-learning","pca-algorithm","python","svm-classifier"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/RobCyberLab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-16T20:34:34.000Z","updated_at":"2024-11-17T09:51:13.000Z","dependencies_parsed_at":"2024-11-20T13:17:39.163Z","dependency_job_id":null,"html_url":"https://github.com/RobCyberLab/Machine-Learning-Classifier","commit_stats":null,"previous_names":["robcyberlab/machine-learning-classifier"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RobCyberLab%2FMachine-Learning-Classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RobCyberLab%2FMachine-Learning-Classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RobCyberLab%2FMachine-Learning-Classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RobCyberLab%2FMachine-Learning-Classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RobCyberLab","download_url":"https://codeload.github.com/RobCyberLab/Machine-Learning-Classifier/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246458022,"owners_count":20780675,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","artificial-intelligence","classifiers","data-analysis","data-science","deep-learning","digit-recognition","machine-learning","pca-algorithm","python","svm-classifier"],"created_at":"2024-12-13T12:35:16.143Z","updated_at":"2025-03-31T10:50:53.399Z","avatar_url":"https://github.com/RobCyberLab.png","language":"Python","readme":"# 🤖Machine Learning Classifier⚙️\n\nA Python implementation of handwritten digit recognition using Support Vector Machine (SVM) and Principal Component Analysis (PCA).\n\nNote: Due to privacy policies, I am not allowed to post the dataset publicly.\n\n---\n\n## Table of Contents📋\n- [Overview](#overview)\n- [Dependencies](#dependencies)\n- [Dataset](#dataset)\n- [Implementation](#implementation)\n- [Running the Code](#running-the-code)\n- [Experimentation](#experimentation)\n\n---\n\n## Overview📝\nThis project implements a machine learning pipeline for recognizing handwritten digits using the following techniques:\n- Dimensionality reduction with PCA\n- Classification using linear SVM\n- Performance evaluation on validation set\n\n---\n\n## Dependencies🛠️\n```python\nfrom sklearn.datasets import load_digits\nfrom sklearn.decomposition import PCA\nfrom sklearn import svm\n\n```\n\n---\n\n## Dataset📂\nThe project uses the Digits Dataset from scikit-learn, which contains:\n- Handwritten digit images (0-9)\n- Features extracted from the images\n- Target labels indicating the digit\n\n---\n\n## Implementation💻\n\n### 1. Data Loading\n```python\ndigits = load_digits()\nx, y = digits.data, digits.target\n```\n\n### 2. Dimensionality Reduction\n```python\npca = PCA(n_components=8)\npca.fit(x)\nx = pca.transform(x)\n```\n\n### 3. Model Training and Prediction\n```python\nsvc = svm.SVC(kernel='linear')\nsvc.fit(x_train, y_train)\ny_predicted = svc.predict(x_valid)\n```\n\n---\n\n## Running the Code▶️\n1. Load the digits dataset\n2. Apply PCA transformation\n3. Split data into training and validation sets\n4. Train SVM classifier\n5. Make predictions and evaluate performance\n\n---\n\n## Experimentation⚗️\nThe following parameters can be modified to optimize performance:\n- Number of PCA components\n- Training set size\n- SVM kernel and parameters\n\nLearning curves can be plotted to visualize the impact of:\n- Number of PCA components vs. accuracy\n- Training set size vs. accuracy","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobcyberlab%2Fmachine-learning-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frobcyberlab%2Fmachine-learning-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobcyberlab%2Fmachine-learning-classifier/lists"}