GitHub topics: random-forest-regression

Repositories

kaylaipp/Linking-Writing-Processes-to-Writing-Quality

Linking Writing Processes to Writing Quality

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Jayita11/Flight-Price-Prediction-ML

A machine learning model predicts flight prices based on factors like departure date, airline, and number of stops. Deployed with Streamlit, the app provides quick price predictions based on user input.

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shreenidhi7700/Auto_Price_Prediction

We are required to use Machine Learning algorithms to predict the price of cars with the available independent variables such as Horsepower, no-of-cylinders, engine-type, city_mpg, highway_mpg etc.

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marielgyap/Spot-the-Hits

My capstone project for the Institute of Data investigates the metadata of songs on Spotify, building a predictive model to project a track's popularity on Spotify using its audio features.

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zjmagou/MLYPGrain2024

Method Implementations for the ConvAE-RF modelling of grain yield in the mid-lower Yangtze plains

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mdlarson/Taxi-Fare-Prediction-C964

Machine learning student project for NYC Taxi Fare prediction

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Maoelan/co2-emission-prediction

Dicoding Submission Machine Learning Terapan

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Virendra9824/Laptop-Price-Predictor

Machine Learning Project on Laptop Price Prediction

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Asifdotexe/StoDir

Stock direction forecasting model to forecast trends based on the closing price for each day

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IsmaelMousa/house-price-prediction

End to end machine learning pipeline for house price prediction, including exploratory data analysis, data preprocessing, models training & evaluating

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Rakesh-konne/MentalfitnessTracker

Developed a user-friendly interface for individuals to track their mental fitness levels .This utilized machine learning algorithms such as linear regression model and Random Forest Regression model to analyze various inputs and detect pattern and trends.

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tboudart/Life-Expectancy-Regression-Analysis-and-Classification

I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The regression models were fitted on the entire dataset, along with subsets for developed and developing countries. I tested ordinary least squares, lasso, ridge, and random forest regression models. Random forest regression performed the best on all three datasets and did not overfit the training set. The testing set R2 was .96 for the entire dataset and developing country subset. The developed country subset achieved an R2 of .8. I tested seven different classification algorithms to classify a country as developing or developed. The models obtained testing set balanced accuracies ranging from 86% - 99%. From best to worst, the models included gradient boosting, random forest, Adaptive Boosting (AdaBoost), decision tree, k-nearest neighbors, support-vector machines, and naive Bayes. I tuned all the models' hyperparameters. None of the models overfitted the training set.

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Simran2911/Flight-Price-Pridiction

This github repositiory contains the Flight Price Prediction project aims to develop a machine learning model to predict flight ticket prices based on various factors such as departure and arrival locations, dates, airlines, and other relevant features.

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J0joFra/Shopping_Behavior

Analisi di dati relativi ai comportamenti di acquisto dei clienti per estrarre informazioni utili e fornire insights dettagliati.

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Danishyousuf19/Decision-Tree-and-Random-Forest

This contains all the project in which i have used Decision Trees and Random Forest to Predict output

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paschalugwu/alx-data_science-regression

Agricultural Yield and Population Forecasting: Utilizing machine learning to enhance crop yield and predict global population trends, informing sustainable development and policy decisions.

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verrenangelinasaputra/Monelytics-Stock-Prediction

Monelytics is a web-based platform utilizing Python for stock prediction purposes. It compares approximately nine machine learning and deep learning models and can predict the closing prices of the big four Indonesian banks

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mvharsh/Productivity-Predictor

A Flask application to predict the productivity of garment manufacturing employees using a pre-trained Random Forest Regressor model and XGBoost classification model. This tool helps optimize processes and improve overall efficiency in the garment industry.

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bma114/Corroded_Beam_Bending_Prediction

This repository enables an engineer to generate predictions for the mechanical bending performance of corroded beams, using a database of 725 corroded beams tested under monotonic bending. Outputs include the maximum bending moment, residual capacity percentage, yield load, yield displacement, and ultimate displacement.

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maciej-zieniewicz/predict_cereal_ml

A simple project to familiarize with knn and RF classification and regression models.

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tatianacarcamoreula/Prediccion_de_Precio_Bienes_Raices

Predecir el precio de una casa dependiendo de sus características

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BaffinLee/Walmart-Weekly-Revenue-Prediction

Analyze Walmart weekly sales data and build a model to predict weekly sales.

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binhvu3/Salmon-Analysis

Predict Alaska's Salmon population using various Machine Learning models

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Tamiir/TIPE

Mon Travail à Initiative Personnelle Encadré (TIPE) sur le thème de la ville pour mon parcourt en MP.

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masadeghi/EHRsample

Prediction of hospital stay duration in heart failure patients using machine learning.

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manjit-baishya-datascience/NYC-Taxir-Fair-Prediction

This project aims to predict taxi fare amounts in New York City using a dataset of historical taxi rides. We employ machine learning techniques to create models that can estimate the total fare amount based on various features of the trips.

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DanLeiria/taxi_fare_random_forest

Analyze 2013 NYC taxi journey data to predict fares and tips using regression trees and random forests.

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lakshmid13579/Regressions_Other_Python

Regression models other than linear and multiple in Python

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ablacan/ml-ci

A machine learning method for confidence interval (CI) computation with specific application to Covid-19 forecast on 54 countries.

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Shubham235Chandra/HomeScope

HomeScope is an end-to-end data science project that predicts California's median house prices using a Random Forest Regressor. It offers detailed data preprocessing, a user-friendly Streamlit interface, and full deployment guidance, serving as a comprehensive tool for real estate market analysis.

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ZobayerAkib/STudent-Result-Data-Analysis__Data-Analysis-Project

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sanhiitaa/salary-prediction

End-to-End Machine Learning project I made as a machine learning intern @ Mentorness

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Akash1070/BigMart-Sales-Prediction-

Building BigMart Sales Prediction

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SheidaAbedpour/Regression-Credit-Limit-Prediction

Perform regression analysis to predict credit limits using machine learning methods, employing techniques such as feature encoding, scaling, selection, and multicollinearity handling to preprocess data.

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JonasBlancke/Thesis_machine_learning_urban_temperatures

code of master's thesis Jonas Blancke

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ishita48/Machine-Learning_Model_Predicting_California_Housing_Prices

This project employs machine learning to forecast housing prices in California. By scrutinizing location, housing details, and demographics, it constructs various regression models like Linear Regression, KNN, Random Forest, Gradient Boosting, and Neural Networks. These models offer invaluable insights to optimize predictive real estate investment

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agustinportilla/Bone_Mineral_Density

Applying different algorithms (RandomForest, K-NearestNeighbors and LogisticRegression) to predict target and compare their results.

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kashifmughal05/Flight_Price_Prediction_using_ML

In this notebook, I have done Data Cleaning, Data Wrangling, EDA and Feature Engineering. After that I trained the dataset using Machine Learning Algorithm Random Forest Regressor.

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AbbasPak/K-Means-Clustering-in-psychology-Case-study

K-Means Clustering for the coping strategies of Brief COPE Questionnaire

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Anotherafael/STUDY_HousePricePrediction

Web application that utilizes a linear prediction model to analyze the USA Houses Price dataset. The trained model can predict the price of a house based on criteria such as location, number of bedrooms, number of bathrooms, and lot size.

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DrPoojaAbhijith/Project-Predicting-flight-booking-prices.

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Ahmad-Ali-Rafique/Random-Forest-Regressor-Modeling

Detailed exploration of random forest regressors, including data cleaning, model building, and performance evaluation on various datasets.

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astonglen/AirBnb-Price-Prediction

The ability to predict prices and features affecting the appraisal of property can be a powerful tool in such a cash intensive market for a lessor. Additionally, a predictor that forecasts the number of reviews a specific listing will get may be helpful in examining elements that affect a property's popularity.

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giannis9696/healthcare---stroke

Machine learning model that predicts stroke events.

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tedoaba/House-Price-Prediction-App

House-Price-Prediction-App

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nnamanx/f1_strategy_optimization

we aim to predict the finishing positions and very first pit stop lap in Formula 1 races based on a set of features derived from driver statistics, circuit characteristics, and race conditions

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RezaSaadatyar/Time-Series-Analysis-in-Python

This repository contains Python functions for predicting time series.

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dyavadi8769/Student_Performance_Indicator_AWS_CI-CD

This repository contains a machine learning model aimed at predicting student performance across various metrics. Utilizing a diverse set of Machine Learning Regression algorithms, the model predicts scores based on demographic and academic variables.This project demonstrates robust approach to leveraging machine learning for educational outcomes.

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jhylin/ML2-2_random_forest

Machine learning series 2.2 on random forest

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Annarhysa/CrimeHawk

An end-to-end application for crime rate detection and crime type classification

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Praddysingh568/Prediction-of-Student-Alcoholism-and-Academic-Performance

This repository presents a study on predicting student alcoholism and academic performance using machine learning. By analyzing a dataset of student attributes, we develop models to forecast academic outcomes and alcohol usage.

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dyavadi8769/Student_Performance_Indicator_ML_AWS_CI-CD_Pipelines

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NajiAboo/Used_Car_Prediction

Kaggle Used Car Prediction

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damaniayesh/Analytics-in-Sales

The project provides a predictive model for forecasting product sales at specific stores, aiming to optimize inventory management and enhance profitability by leveraging data-driven insights.

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LuluW8071/Laptop-Price-Prediction

A collection of machine learning models for predicting laptop prices

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juliaobenauer/Used-car-price-prediction-with-ML

Udemy Machine Learning project

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kristpapadopoulos/house-price-predictions

Tensorflow Lattice Regression for predicting house prices

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yash-gajjjar/Weather-Forecasting-Supervised-ML

Used Random Forest, Decision Tree, Logistic Regression, and Supervised ML Algorithm

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MaxiRuess/ML_101

Different ML Algorithms both in scripts & Jupyter Notebooks

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soumizde/insurance_prediction

Insurance Premium Prediction

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ameyapatil2002/Used-Car-Price-Prediction--ML-model

This project implements a system for predicting the price of used cars using the Random Forest Regression algorithm. The system is designed to take in various features of a used car and predict its market value.

Language: Python - Size: 1.04 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Immanuel04/Overall-Ratings-and-Salary-Prediction-of-FIFA-22-Players-using-Random-Forest-algorithm

Applying a logical model, represent by the Random Forest algorithm, enhances the analysis of the FIFA 22 dataset. Random Forest serves as a potent tool for analyzing and predicting player performance.

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subashksf/housing-price-prediction

Housing price prediction regression model

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TheklaTr/Parkinsons-Telemonitoring-ML-Project

Project course from CS-C3240 - Machine Learning D in Aalto University

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gokulnpc/Calories-Burnt-Prediction

This web app is created to predict the calories burnt based on the user inputs such as gender, age, height, weight, duration, heart rate, and body temperature. The model used in this web app is a Random Forest Regressor model trained on the dataset with 15000 samples.

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purrvaja/Regression-Analysis

Regression analysis to predict the house prices, along with exploratory data analysis answering research questions

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dorianDraper/California-Housing-Prices

This is the dataset used in the second chapter of Aurélien Géron's recent book 'Hands-On Machine learning with Scikit-Learn and TensorFlow'. It serves as an excellent introduction to implementing machine learning algorithms

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vkotiyal/car-price-predictor

This is system that predicts the estimated selling price of your car. (Undeployed yet)

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gokulnpc/Medical-Insurance-Cost-Prediction

This web app is created to predict the medical insurance cost based on the user inputs such as age, sex, BMI, children, smoker and region. The model used in this web app is a Random Forest Regressor model. The model is trained on the Medical Insurance dataset from Kaggle. The dataset contains 1338 rows and 7 columns.

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upenc/OIBSIP

Repository for Data Science Internship at Oasis Infobyte.

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Abdumajidhu/Classification-and-Regression-using-sklearn

Regression and Classification task with sklearn.

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lfaferreira/predict-rossmann-store-sales

🏪 The project's idea is to use a machine learning model to predict the sales quantity that each store will have in the next six weeks, assisting managers in their future decision-making.

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Pratik-Aher/Flight-Fare-Prediction

The main goal is to predict the fares of the flights based on different factors available in the provided dataset.

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somjit101/NYC-Taxi-Demand-Prediction

This is a Time Series Forecasting and Regression solution to project the no. of pick-ups at and around a given region at a given time in the city of New York, USA.

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danieldutu/LR_EDA_Models

EDA & Linear Regression Models

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RohitG57/Taxi-Fare-Prediction

Aim of this project is to predict taxi fare based on available data. This dataset contains total 8 variables and 50000 indexes.

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Cafarli/RegressionModels

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kaiquefreire05/car-prices-prediction-regression

- Notebook for car price prediction using regression models.

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craigxiangfu/CRP-ML

Code for BU CDS DS 110 Final Project

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Hishok/Impact-of-News-Headlines-on-Stock-Indices

Investigate the impact of general news headlines on Stock Indices

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czarina-ds/regression-analysis-for-estimating-prices Fork of westonshuken/King-county-housing-analysis

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rishabh1882/Classification-with-Random-Forest

A GitHub repository featuring a Random Forest-based prediction model for accurate forecasting of outcomes.

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rociobenitez/AirbnbPricingModel

A Machine Learning exploration evaluating various models to predict Airbnb prices, culminating in an optimized Gradient Boosting Regressor.

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JulienSimons/Home-loan-discrimination

Random forest machine learning regression and interactive web application using home loan data to help determine algorithmic discrimination toward race and gender in the application process. Visit the website: https://juliensimons.shinyapps.io/home-loan/

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ritu-thombre99/Feature-selection-using-Genetic-Algorithm-for-Random-Forest-Classifier-

This project involved implementation of genetic algorithm for feature selection which were then passed to random forest classifier to predict trading position for day trading in Equity stock markets to provide an alternate method for current method used in buy and sell model.

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