There are 3 repositories under support-vector-regression topic.
Learning to create Machine Learning Algorithms
Implementation of Accurate Online Support Vector Regression in Python.
This project utilizes machine learning algorithms to find the direction in which a person is looking by using the face landmarks
Photovoltaic power prediction based on weather data for my bachelor thesis
In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
Automated Essay Scoring on The Hewlett Foundation dataset on Kaggle
In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).
NTHU EE6550 Machine Learning slides and my code solutions for spring semester 2017.
Stock Price Prediction of any Organizations using SVR
Implementation of Regression Models on Navigation with IMUs.
Calibration of an air pollution sensor monitoring network in uncontrolled environments with multiple machine learning algorithms
The project aims to develop models that can forecast traffic congestion, aiding in effective traffic management and planning.
Explanation of Mathematics used in Machine Learning Algorithms and some Projects
Capstone Project Gold Price Prediction using Machine learning Approach for Udacity Machine Learning engineer Nanodegree Program
Predict using ML the number of infected people and the number of deaths of coronavirus.
Computer Intelligence subject final project at UPC.
My solution to House-Prices Advanced Regression Techniques, A beginner-friendly project on Kaggle.
Age Estimation via fastAAMs
Datasets and code to accompany Briceno-Mena, Luis A. and Venugopalan, Gokul and Romagnoli, José A. and Arges, Christopher G., Machine Learning for Guiding High-Temperature PEM Fuel Cells with Greater Power Density. Available at https://www.cell.com/patterns/fulltext/S2666-3899(20)30257-9
A very basic Support Vector Regression model implemented in python
Global Horizontal Irradiance Analysis using Support Vector Regression and Bayesian Ridge Regression
Time Series data Analysis of Rainfall in Bangladesh
Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.
The performance of SVR models highly depends upon the appropriate choice of SVR parameters. Here, different metaheuristic algorithms are used to tune the hyperparameters.
This project is an implementation of hybrid method for imputation of missing values
Remaining useful life (RUL) prediction of cutting tools is critical to effective condition based maintenance for reducing downtime, ensuring quality and avoiding accidents. we worked on a research paper to build a Machine Learning model for predicting the remaining useful life of cutting tools. Extracted different features from the dataset and developed an algorithm by using Support Vector Regression for the prediction of RUL.
Using ε-Support Vector Regression (ε-SVR) for identification of Linear Parameter Varying (LPV) dynamical systems
This project aims to estimate head pose via face 2D landmarks using machine learning.
Machine Learning algorithms implementation using Python
Comparative Evaluation of Non-Conventional Value Function Approximation Methods in Reinforcement Learning