GitHub topics: tree-based-methods
annalisaxamin/SL_homeworks
Homeworks for Statistical Learning course (Prof. Vinciotti) @ University of Trento
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KarimABOUSSELHAM/ISLP-applied-solutions
Solutions of applied exercises contained in "An Introduction to Statistical Learning with Applications in Python", by Tibshirani et al, edition 2023
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CN-TU/machine-learning-in-ebpf
This repository contains the code for the paper "A flow-based IDS using Machine Learning in eBPF", Contact: Maximilian Bachl
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LucasO21/seoul-bikeshare-prediction
A machine learning project, predicting hourly bike rentals in Seoul.
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Alex-Mak-MCW/Deposit_Subcriptions_Predictions_Project
Group academic research project focuses on predicting term deposit subscriptions for bank clients through data science, data analytics, and machine learning.
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gabrieldeolaguibel/ML-Projects
A collection of various applied Machine Learning and Artificial Intelligence projects I have done.
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FilomKhash/Tree-based-paper
Codes for the paper On marginal feature attributions of tree-based models
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tohid-yousefi/Prediction_Diabetes_Using_Classification_Machine_Learning_Algorithms
In this section we will be predicting diabetes using classification machine-learning algorithms
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lakshyaag/ML-Tree-Based-Algorithms
Implementing Tree-based algorithms from scratch (Decision Tree, Random Forest, and Gradient Boosting) from scratch and comparing it to the scikit-learn implementation.
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yuvalofek/FrequentistML
Linear & logistic regression, model assessment and selection, and gradient boosted trees
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eiliaJafari/tree-based-customer-churn-rate
Tree methods for customer churn prediction. Creating a model to predict whether or not a customer will Churn .
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owenpb/Kaggle-Bike-Sharing-Prediction
Kaggle competition: predicting bikeshare demand with regression techniques. Linear/Lasso/Ridge Regression, KNN, Decision Tree, Random Forest, AdaBoost, XGBoost.
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owenpb/Kaggle-Forest-Cover-Prediction
Kaggle competition: predicting forest cover type with multiclass classification algorithms. Logistic Regression, SVC, KNN, Decision Tree, Random Forest, XGBoost, AdaBoost, LightGBM, & Extra Trees.
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aubin-tchoi/flappy_bird
Tree-based algorithms for solving a game of Flappy Bird.
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Marmingen/SML-lead-analysis
Analyzing the binary gender difference in lead roles using statistical machine learning
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sliao7/CSE6740_Computational_Data_Analysis
All the course work of supervised and unsupervised algorithms and projects.
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SANTONLA/INTRODUCTION-TO-MACHINE-LEARNING-WITH-R
This is a repository with exercises extracted from the book "Introduction to machine learning with R" from Scott V. Burger. It will help you gain a solid foundation in machine learning principles. Using the R programming and then move into more advanced topics such as neural networks and tree-based methods.
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tugrulhkarabulut/Tree-Based-Methods
Implementation of Decision Tree and Ensemble Learning algorithms in Python with numpy
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Lindahe0707/Customer-Loyalty-Analysis-From-Purchasing-Behavior
This is a customer loyalty analysis based on historical purchase behavior in R language.
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abhiram-ds/telecom_churn_case_study
Telecom Churn analysis using various tree based classification models
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