Brave Search

The package includes the source code of the library in C++ and Java, and a simple program for scaling training data. A README file with detailed explanation is provided. For MS Windows users, there is a sub-directory in the zip file containing binary executable files.

LIBSVM

Library for Support Vector Machines

csie.ntu.edu.tw

LIBSVM and LIBLINEAR are two popular open source machine learning libraries, both developed at the National Taiwan University and both written in C++ though with a C API. LIBSVM implements the sequential … Wikipedia

Factsheet

Developers Chih-Chung Chang and Chih-Jen Lin

Stable release 3.3
/ August 11, 2022; 3 years ago (2022-08-11)

Written in Java, C++

Factsheet

Developers Chih-Chung Chang and Chih-Jen Lin

Stable release 3.3
/ August 11, 2022; 3 years ago (2022-08-11)

Written in Java, C++

GitHub

gist.github.com › mblondel › 586753

Support Vector Machines · GitHub

if anyone is interested in a possible implementation of an SVR according to the pdf linked by @guruprasaad123, they can find the code here: https://github.com/dmeoli/optiml/blob/master/optiml/ml/svm/_base.py

Discussions

Unable to delete a SVM Peer relationship

Sounds like you need to do exactly what it’s suggesting. There’s a relationship somewhere that you removed on the destination via “snapmirror delete” but didn’t do “snapmirror release” on the source cluster. It won’t show up in “snapmirror show” which is why you need to use “snapmirror list-destinations” to find it. More on reddit.com

r/netapp

March 11, 2020

Reversing SVM-DR source/target clusters?

You fail it over then you rebuild the snapmirror back to the other site until you're ready to fail back. More on reddit.com

r/netapp

March 5, 2025

SVM Classifier in Python using Numpy (Video & GitHub)

In this video, we go over the math & intuition of hard-margin and soft-margin SVMs. In soft-margin, we take a look at the decision boundary, margin… More on reddit.com

r/Python

January 20, 2024

NEED HELP WITH SVM KERNEL CODE IN PYTHON FROM SCRATCH

Ask ChatGPT. It knows how to implement basic things. "I want to implement that, what would be the different steps in my program" then you ask more questions like "how do I write the kernel function" and so on. Just like when you program yourself, it's all about turning big problems into a sequence of smaller and simpler problems. If chat GPT can't directly solve the big problem, tell chat GPT to give you several steps and then ask chat GPT to solve a step. More on reddit.com

r/learnmachinelearning

December 13, 2023

scikit-learn

scikit-learn.org › stable › modules › svm.html

1.4. Support Vector Machines — scikit-learn 1.8.0 documentation

The support vector machines in scikit-learn support both dense (numpy.ndarray and convertible to that by numpy.asarray) and sparse (any scipy.sparse) sample vectors as input. However, to use an SVM to make predictions for sparse data, it must have been fit on such data.

GitHub

github.com › cjlin1 › libsvm

GitHub - cjlin1/libsvm: LIBSVM -- A Library for Support Vector Machines · GitHub

For example, 25 0:3 1:1 2:0 3:1 45 0:2 1:6 2:18 3:0 implies that the kernel matrix is [K(2,2) K(2,3)] = [18 0] [K(3,2) K(3,3)] = [0 1] Library Usage ============= These functions and structures are declared in the header file `svm.h'. You need to #include "svm.h" in your C/C++ source files and link your program with `svm.cpp'.

Starred by 4.7K users

Forked by 1.6K users

Languages Java 21.8% | C++ 18.7% | HTML 17.9% | M4 13.9% | Python 13.5% | C 13.3%

GitHub

github.com › cperales › SupportVectorMachine

GitHub - cperales/SupportVectorMachine: Python implementation of Support Vector Machine (SVM) classifier

Python implementation of Support Vector Machine (SVM) classifier - cperales/SupportVectorMachine

Starred by 11 users

Forked by 13 users

Languages Python 100.0% | Python 100.0%

GitHub

github.com › theogf › BayesianSVM

GitHub - theogf/BayesianSVM: Source code of the Bayesian SVM described in the paper by Wenzel et al. "Bayesian Nonlinear Support Vector Machines for Big Data"

This repository contains the updated source code for the Bayesian Nonlinear Support Vector Machine (BSVM) both in its stochastic (and with inducing points) and its batch version

Starred by 19 users

Forked by 8 users

Languages Julia 100.0% | Julia 100.0%

scikit-learn

scikit-learn.org › stable › modules › generated › sklearn.svm.SVC.html

SVC — scikit-learn 1.8.0 documentation

class sklearn.svm.SVC(*, C=1.0, kernel='rbf', degree=3, gamma='scale', coef0=0.0, shrinking=True, probability=False, tol=0.001, cache_size=200, class_weight=None, verbose=False, max_iter=-1, decision_function_shape='ovr', break_ties=False, random_state=None)[source]#

Python Data Science Handbook

jakevdp.github.io › PythonDataScienceHandbook › 05.07-support-vector-machines.html

In-Depth: Support Vector Machines | Python Data Science Handbook

The text is released under the CC-BY-NC-ND license, and code is released under the MIT license. If you find this content useful, please consider supporting the work by buying the book! < In Depth: Linear Regression | Contents | In-Depth: Decision Trees and Random Forests > Support vector machines (SVMs...

Find elsewhere

Google Bing Mojeek

GitHub

github.com › mahesh147 › Support-Vector-Machine

GitHub - mahesh147/Support-Vector-Machine: A simple implementation of support vector machine classifier in python. · GitHub

A simple implementation of support vector machine classifier in python. - mahesh147/Support-Vector-Machine

Starred by 44 users

Forked by 78 users

Languages Python

Analytics Vidhya

analyticsvidhya.com › home › how to use support vector machines (svm) in python and r

How to Use Support Vector Machines (SVM) in Data Science?

June 16, 2025 - The e1071 package in R is used to create SVM in data mining with ease. It has helper functions as well as code for the Naive Bayes Classifier. The creation of a support vector machine algorithm in R and Python follows similar approaches.

GitHub

github.com › pb111 › Support-Vector-Machines-Project

GitHub - pb111/Support-Vector-Machines-Project: Support Vector Machines with Python Project · GitHub

Support Vector Machines with Python Project. Contribute to pb111/Support-Vector-Machines-Project development by creating an account on GitHub.

Starred by 9 users

Forked by 5 users

Languages Jupyter Notebook

Cornell Computer Science

cs.cornell.edu › people › tj › svm_light › svm_perf.html

SVM-perf: Support Vector Machine for Multivariate Performance Measures

Includes Nystrom and incomplete Cholesky methods for approximate training of kernel SVMs. Source code for SVMperf V2.50.

GitHub

github.com › junbolian › SVBM

GitHub - junbolian/SVBM: The source code of Support Vector Boosting Machine (SVBM): Enhancing Classification Performance with AdaBoost and Residual Connections · GitHub

The source code of Support Vector Boosting Machine (SVBM): Enhancing Classification Performance with AdaBoost and Residual Connections - junbolian/SVBM

Author junbolian

GitHub

github.com › karpathy › svmjs

GitHub - karpathy/svmjs: Support Vector Machine in Javascript (SMO algorithm, supports arbitrary kernels) + GUI demo

Can be found here: http://cs.stanford.edu/~karpathy/svmjs/demo/ Corresponding code is inside /demo directory.

Starred by 702 users

Forked by 151 users

Metana

metana.io › metana: coding bootcamp | software, web3 & cyber › ai & machine learning › svm classifier in python: full step-by-step implementation

Implementing Support Vector Machine (SVM) Classifier in Python - Metana

July 12, 2024 - Discover how to implement the Support Vector Machine (SVM) classifier in Python. Learn step-by-step the process from data preparation to model evaluation.

GitHub

github.com › scikit-learn › scikit-learn › tree › main › sklearn › svm

scikit-learn/sklearn/svm at main · scikit-learn/scikit-learn

scikit-learn: machine learning in Python. Contribute to scikit-learn/scikit-learn development by creating an account on GitHub.

Author scikit-learn

Stack Abuse

stackabuse.com › implementing-svm-and-kernel-svm-with-pythons-scikit-learn

Implementing SVM and Kernel SVM with Python's Scikit-Learn

July 2, 2023 - from sklearn.svm import SVC svc = SVC(kernel='linear') This way, the classifier will try to find a linear function that separates our data. After creating the model, let's train it, or fit it with the train data, employing the fit() method and giving the X_train features and y_train targets as arguments. We can execute the following code in order to train the model:

Wiley Online Library

ietresearch.onlinelibrary.wiley.com › doi › 10.1049 › sfw2 › 7163249

Design Pattern Prediction From Source Code Using LLM–Based Feature Engineering and SVM Classification - Komolov - 2026 - IET Software - Wiley Online Library

January 16, 2026 - Step 8: Classify the integrated response using SVM to detect design patterns, that is, C({Ri}) = yi, where yi is the predicted class label (design pattern) for a document (source code) i.

Cornell Computer Science

cs.cornell.edu › people › tj › svm_light › svm_struct.html

SVM-Struct Support Vector Machine for Complex Outputs

SVMstruct Matlab: A matlab interface to the SVMstruct API for implementing your own structured prediction method. Again, prototyping should be much easier and faster than working in C. More information and source code.

Medium

medium.com › deep-math-machine-learning-ai › chapter-3-1-svm-from-scratch-in-python-86f93f853dc

Chapter 3.1 : SVM from Scratch in Python. | by Madhu Sanjeevi ( Mady ) | Deep Math Machine learning.ai | Medium

May 9, 2018 - Last story we talked about the theory of SVM with math,this story I wanna talk about the coding SVM from scratch in python. Lets get our hands dirty! Full code is available on my Github.