bandframework/Taweret

Python package for Bayesian Model Mixing

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jespb/Python-StdGP

An easy-to-use scikit-learn inspired implementation of the Standard Genetic Programming (StdGP) algorithm.

Language: Python - Size: 38.1 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 8 - Forks: 9

RufelleEmmanuelPactol/16PF-Analysis-Deep-Ensemble-Learning

[Published, Macau, ICETT] EDA, and model development of utilizing 16 PF data for decision support systems in higher-level education. Utilizes "Augmented Clustering" and "Deep Ensemble Learning"

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chicago-joe/Python-ML-for-Financial-Applications

Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling

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Snigdho8869/Regression-Analysis-Projects

Repository showcasing a collection of diverse regression analysis projects including salary prediction and more.

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serengil/decision-trees-for-ml

Building Decision Trees From Scratch In Python

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Arek-KesizAbnousi/Neural_Networks

Fit four different neural networks: (a) Two distinct single hidden layer neural networks. (b) Two distinct neural networks with two hidden layers. Compare the accuracy of these four Neural networks among them. Also compare it to other classification methods.

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Entscheider/stamm

Generic decision trees for rust

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mpfarrho/mf-bavart

MF-BAVART model introduced in "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs"

Language: R - Size: 1.83 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 30 - Forks: 16

winkjs/wink-regression-tree

Decision Tree to predict the value of a continuous target variable

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xgagandeep/Machine-Learning-Algorithms-without-using-ML-libraries.

This repository contains various links for repo for implementations of machine learning algorithms from scratch using Python

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ericyoc/ml_portfolio_poc

A portfolio of machine learning algorithms that are essential and commonly used.

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AtheerAlzhrani/ml-projects

ML projects, which I worked on utilising different machine learning algorithms.

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RogerioLS/Scikit-Learn

:mortar_board: Curso com os criadores do Scikit-Learn

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ramironunes/regression-trees

This repository explores regression trees for predictive modeling. It covers theory, practical implementations, and model optimization. Using Python and scikit-learn, it demonstrates tree-based regression on real-world datasets, focusing on model accuracy and interpretability.

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AmbreenMahhoor/Decision-Trees-And-Regression-Trees

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TeFuirnever/Machine-Learning-in-Action

⚡️⚡️⚡️《机器学习实战》代码（基于Python3）🚀

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hpclab/rankeval

Official repository of RankEval: An Evaluation and Analysis Framework for Learning-to-Rank Solutions.

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aye-shadow/machine-learning-practise

This repo is for all my machine-learning mini-projects to showcase my learning as I dive into the world of AI/ML/DL.

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atharvapathak/Sales_Forecasting_Project

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

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gustavecortal/statistical-learning-with-R

Slides, exercises, and exams for my course "Statistical Learning with R" (Ecole Normale Supérieure Paris-Saclay, 2023)

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DinisDimitris/Net-ecosystem-exchange-Quantification

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brigittesullivan/eps-stock-market-ml-project

Machine learning project that predicts the percent change in stock price after next earnings event for public companies. Completed as a Riipen Data Science Internship.

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mrsergazinov/cartcpp

Implementation of CART and Random Forest in C++

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hb1500/Wikileaks-Stock-Market-1 Fork of o9812/Wikileaks-Stock-Market

Machine Learning course term project, collaborated with Dr. Daniel Chen, and Dr. Elliot Ash

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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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vokereke/uswages_trees_randomforest

Predicting wage in the uswage dataset (Regression Tree & Random Forest)

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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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beingwaseem/Taxi-Tip-Prediction-using-Scikit-Learn-and-Snap-ML

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Enr-MorenoSchz/ML-Solar-Prediction-2023 📦

[ Machine Learning ] 1st Practice re-uploaded. Co-Author: @Devinchy

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diesing-ngu/GSMgrids

Workflow to spatially predict mud (silt and clay) content of seafloor surface sediments in Norway

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suzanaiacob/Tree-Methods

Projects using tree methods (CART, Random Forests, Boosted Trees)

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ayigitdogan/Decision-Trees-Regression-Example

Predicting Toyota Corolla prices with R

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Arek-KesizAbnousi/Random_Forest

Tuning Random Forests, comparing their classification accuracy to Regression Trees.

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ogru/fTree

An R package that implements several methods for growing regression trees with functional and multivariate outputs

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fbalensiefer/Machine_Learning_R

Statistical Learning in R

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starryjay/PSTAT131Final

This is the repository for my R project on modeling historical weather data in Santa Barbara.

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kaigg96/Driving-Towards-Efficiency

Using Python and the Natural Resources Canada Fuel Consumption Ratings to view and predict vehicle efficiency.

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30lm32/ml-time-series-analysis-on-sales-data

Time Series Decomposition techniques and random forest algorithm on sales data

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Data-Science-kosta/Forecasting-air-pollution-LSTM-model-and-Regression-trees-model

Forecasting air pollution from given weather data. Two models were implemented: Regression Trees and LSTM model.

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dkohlsdorf/GradientBoostedTrees

Simple Implementation of Gradient Boosted Trees

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mbsuraj/All-Regression-Trees

All regression tree models in one place

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vargovema/real-estate-demand-ml

Predicting the Demand for Real Estate Listings in Austria

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micheleandreucci/Regression-Tree

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jsrpy/NYC-Property-Regression

A real life case study of property price prediction based on data of New York City.

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andremonaco/cheapml

Machine Learning algorithms coded from scratch

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zhousrhhh/Tip-Prediction-for-New-York-Uber-Lyft-Drivers

Tip-Prediction-for-New-York-Uber/Lyft-Drivers

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MeredithGal/Predictive-Analytics-with-R-Programming

UNCW BAN 502 This course explores methods for model selection, parameter estimation, and validation. Focused on techniques and algorithms from the statistical and machine learning disciplines.

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enstit/TweetPopularityPrediction

Project about the use of Supervised (Machine) Learning techniques to predict the popularity of a tweet about food.

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Soullevram/CART

Tree-based data mining algorithmic model for body weight prediction in indigenous Nigerian goat breeds

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sandipanpaul21/Tree-Based-Models-in-Python

Tree based algorithm in machine learning including both theory and codes. Topics including from decision tree regression and classification to random forest tree and classification. Grid Search is also included.

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chethanhn29/Advanced-House-Price-Prediction

The Objective is to use Machine Learning to Build a model to Predict House Price Using Advanced Regression Techniques, With analysis of given quantitative measurements of House.

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0x65-e/Kokomo

Kokomo is a competitor robot built for Robocode that uses regression tree based machine learning (called "Dynamic Segmentation" on the Robocode wiki) for its targeting strategy

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wgurecky/pCRTree

Gradient boosted classification and regression trees in python

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Emeierkeio/machinelearning-predictinghousesprices

🤖🧠 Report and Knime workflow used to predict the King County houses' prices for 2021/22 Machine Learning project @ University of Milano-Bicocca

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datagirlz19/Applied-Data-Science-in-R

A collection of mini projects in R that apply statistical and machine learning methods and tools to solve data-driven problems

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steve303/stat542proj1-regressionTrees

Regression Models - Decision Trees (GBM) and Linear Regression (ElasticNet)

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aldro61/mmit

Regression trees for interval censored output data

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mustafahakkoz/Predict_Transaction_Amount

A submission for Türkiye İş Bankası Machine Learning Challenge #2

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tkhan11/Dtreehub

Dtreehub is a lightweight decision tree framework for Python with categorical feature support. It covers regular decision tree algorithms: ID3, C4.5, CART, CHAID and regression tree, random forest and adaboost.

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bhattbhavesh91/decision-tree-regression

Simple example demonstrating Regression using Decision Trees

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gzlupko/CART

This repo contains an R programming project that implements and compares decision tree models including C5.0, C5.4 and CART.

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melinebel/movieSuccess-RegressionTree

A simple regression tree model to study the interplay between box office, critics and audiences in determining a movie's success.

Language: Python - Size: 163 KB - Last synced at: 4 months ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

geangohn/hybrid_regression_tree Fork of krisbell/hybrid_regression_tree

Hybrid of Regression Trees & Linear Regression

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lyx199504/machine-learning-in-action

《机器学习实战》代码和数据。The code and data of Machine Learning in Action.

Language: Python - Size: 15.1 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 3

gasparian/XGB2Code

Exporting trained boosted trees to executable code in plain C / Python

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fjmillman/machine-learning

An implementation of 4 machine learning algorithms from scratch

Language: Python - Size: 3.34 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

iankurgarg/Parameter-Tuning-Learners

Assignments, Projects and other course related material.

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majacaci00/2016_boston_marathon

What factors influence runners

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