support-vector-regression | Topic

Topic: "support-vector-regression"

dilne/CaliforniaHousing

California Housing Price Prediction - Linear Regression, Support Vector Regression, Decision Trees, and Random Forest Regression

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Sahaj-26/House-Price-Prediction

The project aims to predict house prices in California based on various features using machine learning techniques. It uses the California housing dataset, comprising 20640 data entries and 8 attributes, with the target being the house price.

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wwh9345/Regression-Modeling-US-Airline-On-Time-Performance

This repo contains the project jupyter notebooks and data files to view and re-run my analysis of the flight data.

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Afrid1045/Car_Price_Prediction

Predicting the Car prices based on its features and to help maintain transparency between car sellers and buyers. We can use the website to check the car price without third party interaction.

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farooqueesamiya/Regression-Models-for-Salary-Prediction

In this repository, we will investigate various regression models to predict whether an individual being interviewed is misrepresenting their salary.

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pjukalkar24/bone_age_assessment

In collaboration with Dr. Liang Zhan and the 2022 Hillman Academy. This study implements a Dense Dense U-Net, a convolutional neural network, to segment hand x-rays using K-Means clusters as ground truths. A Support Vector Regression model utilizes produced segmentations to predict bone age with greater speed, precision and accuracy as radiologists

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Coder-Chitta/Machine-Learning-Hands-On-Regression-

Regression

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Tayyba27/Classification

One of the basic data sets to learn and implement some of the most easy and basic algorithms of machine learning and visualization.

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m0hammadjaan/StudentsGradePrediction

Semester Project | NEDUET

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darian-catalin-cucer/support-vector-machines

Support Vector Machines (SVM) is a supervised machine learning algorithm used for classification and regression analysis. It aims to find the best boundary between classes by maximizing the margin between them. SVM is particularly useful in high-dimensional data and can handle non-linear data using a technique called the kernel trick.

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kpsijil2/Cement-Manufacturing

Predicting cement strength

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kpsijil2/Big-Mart-Sales

Predicting Big mart sales

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jaiminjariwala/Random_Forest_Project_1

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Vinicius999/ICU-beds-forecast-covid-19

Predição da ocupação de leitos de UTI no Brasil devido a pandemia do COVID-19, usando Support Vector Regression (SVR)

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guevara-erik/Titanic-disaster-Binary-Classification

Problem to solve: On the Titanic disaster predict who would survive based on 4 features: sex, age, fare and class.

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Animesh-Chourey/Age-Estimation-by-Regression

Age estimation is performed from the facial images.

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FanChiMao/RevisionWork-2022-VQA

No-reference Video Quality Assessment

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BenjaminRueling/Red-Wine-Quality

Kernel-Methods on a Red-Wine Dataset

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programmatoroSeduto/UJI_indoor_loc

a Machine Learning project about WLAN fingerprint localization using explicit threading and sciKitLearn.

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DhruvSrikanth/Superconductor-Regression-Kaggle-Challenge

Kaggle challenge based on superconductor dataset.

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sandipanpaul21/KNN-Naive-Bayes-SVM-in-Python

ML Topics include KNN. Naive Bayes and Support vectors both in Theory and Python Code. KNN Imputation technique is also explained in this branch.

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rimshasaeed/Net-Hourly-Electrical-Power-Prediction-via-Regression

An intelligent and accurate hourly electricity power prediction system developed using ML regression techniques.

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kwilson-tech/Automobile-Price-Prediction

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ramonbotella/RAP-data-RILEM-TCRAP-TG5

Repository with data and code for the prediction of RAP DoA using Compaction Temperature, Air voids and ITS with machine learning techniques

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kwilson-tech/Salary-Predictions-NBA-2K20-

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janerjzou/Predict-the-Area-Size-of-Future-Forest-Fire

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HanifaElahi/Machine-Learning

MACHINE LEARNING ALGORITHMS

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MichaelAlexanderBryant/vehicle-price-rec-app

The front end of a project for predicting vehicle sales prices.

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shwetamustare/Support-Vector-Regression

Minimising the Epsilon Slack variable distance with Support Vector Regression - on salary data with job role and position level as independent variables.

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prabhatk579/machine-learning-algorithms-archive

Implementation of different types of machine learning algorithm and there performance comparison on a same dataset

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tulkot/World-Happiness-Report-Analysis-and-Prediction-Using-R

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kbjornson/credit-analysis

Using customer credit data collected over the past 6 months, build a model to determine whether a customer will default on a credit loan.

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JimRaza/ML-Projects

Machine learning and data science projects in Python

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iam-D-prog/Machine-Learning-SVR

Support Vector Regression

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mocchicone/NASA-Machine-Learning

Created supervised machine learning models capable of classifying candidate exoplanets from the raw dataset. Conducted feature selection and data scaling. Two classification models, Support Vector and Neural Network, were trained, hypertuned, and tested.

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RyanLBuchanan/Support_Vector_Regression

Support Vector Regression tutorial from Machine Learning A-Z - SuperDataScience -> Input by Ryan L Buchanan 18SEP20

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NarmadhaMM/Bayesian-ML-for-occupancy-data

Includes the R code and the supporting materials for our paper "Using machine learning to identify nontraditional spatial dependence in occupancy data"

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kailash-turimella/Regression-Using-Python

Machine Learning Models using Python (Regression)

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kavya76/Microsoft-Codefundoo-2018

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dandeelyon/SVM-SVD

Master's Thesis on Support Vector Machines and Singular Value Decomposition: Using Machine Learning to predict the Sensory Character of Wine.

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Karan-Malik/AdvancedRegression

Using Various Regression Algorithms to Predict House Sales

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sdrttnclskn/tez-calismasi

Makine Öğrenme Metotları Kullanılarak Fonların Fiyat Tahmin için Model Geliştirilmesi

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ayushrox/sedimentation_prediction

Inland Water Transport Aids to Navigation using Sediment Prediction

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gt0410/Predicting_ViolentCrime_Data

Exploratory Data Analysis and Feature Engineering on Violent Crime dataset from Kaggle and performing regression analysis to predict the crime rate per 100k population. This project compared the performances of Linear Regression, PLS, regularized models like Ridge regression, Lasso and Elastic Net models, and SVR models.

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