Custom implementation of Support Vector Machines using Python and NumPy
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Updated
Apr 2, 2020 - Jupyter Notebook
Custom implementation of Support Vector Machines using Python and NumPy
Solving Convex and Nonconvex Optimization Problems
SVM algorithm for handwritten digit classification
Classification of a radially seperated dataset using SVM with RBF kernel using CVXOPT
Compilation of different ML algorithms implemented from scratch (and optimized extensively) for the courses COL774: Machine Learning (Spring 2020) & COL772: Natural Language Processing (Fall 2020)
SVM implementation from scratch in python.
Vectorize the Matlab/CVX for-loops as much as possible. 自动向量化Matlab和CVX的for循环。
The project Epsilon SVR is built from Scratch with minimum Sk Learn packages. This Epsilon SVR improves the SVR Model.
Solving the Character recognition problem as an SVM optimization problem using CVXOPT
Uplift modeling and estimation via the "Uplift Support Vector Machine".
This repo consist of the assignments and other code snippets of the module EN4553.
SVM implementation for Binary and Multiclass classification using standard SVM library and Convex optimastion method
Proposing a novel approach on using Naives Bayes by using Robust Kernel Density Estimation (RKDE) and optimising the bandwith(h) with Harris Hawks Optimization (HHO)
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