svr

Python code for common Machine Learning Algorithms

The R package for SVM with GPU architecture based on the GTSVM software

NTHU EE6550 Machine Learning slides and my code solutions for spring semester 2017.

Photovoltaic power prediction based on weather data for my bachelor thesis

SVR for multidimensional labels

Comparative Analysis of Techniques for Forecasting Time Series in Financial Markets

This repo is an implementation of the research paper "A Data Mining Approach to Predict Forest Fires using Meteorological Data." by P. Cortez and A. Morais. The algorithms used are : SVR, Decision Trees, Random Forests, Simple Deep Neural Network ( Keras with Tensorflow backend)

Based on the SVR interpolation, a new method about the time-varying channel estimation of FBMC is proposed.

Using ε-Support Vector Regression (ε-SVR) for identification of Linear Parameter Varying (LPV) dynamical systems

R codes for common Machine Learning Algorithms

Predict the compensation base on the position level using the SVR machine learning model.

lsgkm+gkmexplain with regression functionality. Builds off kundajelab/lsgkm (which has gkmexplain), which in turn builds off Dongwon-Lee/lsgkm (the original lsgkm repo)

Path planning in aerial images using imitation learning

Course work of Multivariate data analysis CH5440

Ejemplo del tipo de regresión SVR (Regresión de Soporte Vectorial) en python.

Forecasting exchange rates by using commodities prices

Python-Wrapper for Francesco Parrella's OnlineSVR C++ implementation with scikit-learn-compatible interface.

Simple regression problem where by pre-loaded data I have shown different regression algorithm and their performance on data.

Compared different classification and regreesion models performance in scikit-learn by applying them on 20 datasets from UCL website.

Here I upload my ML test scripts written in MATLAB or Python

Stock Price Prediction

Electrical Impedance Spectroscopy analysis using Machine Learning

Dash application to simulate various regression models

Predicting house prices using SVR

A showcase of my own implementations of ML approaches. Created for the MLDS course @ DS Masters, FRI UL.

Common Machine Learning Examples 💻

We have used Support Vector Regression and Random Forest Regression to predict traffic or congestion.

The project Epsilon SVR is built from Scratch with minimum Sk Learn packages. This Epsilon SVR improves the SVR Model.

Multiple randomized ANN are being generated that is being taken from user input(total number of ANN) then we have approached one of the nature-inspired-algorithms such as DIFFERENTIAL-EVOLUTION(DE) on a soil-content-dataset to prove that it has better prediction and optimising values other than some well defined algorithms such as SUPPORT-VECTOR-REGRESSION(SVR) and MLP-REGRESSOR.