KasiMuthuveerappan/CAB-Ensemble-Learning-CHURN-Prediction

📘 This repository predicts OLA driver churn using ensemble methods—Bagging (Random Forest) and Boosting (XGBoost)—with KNN imputation and SMOTE. It reveals city-wise churn trends and key performance drivers, powering smarter, data-backed retention strategies for the ride-hailing industry.

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somjit101/Facebook-Friend-Recommendation

This is a friend recommendation systems which are used on social media platforms (e.g. Facebook, Instagram, Twitter) to suggest friends/new connections based on common interests, workplace, common friends etc. using Graph Mining techniques. Here, we are given a social graph, i.e. a graph structure where nodes are individuals on social media platforms and a directed edges (or 'links') indicates that one person 'follows' the other, or are 'friends' on social media. Now, the task is to predict newer edges to be offered as 'friend suggestions'.

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wiegertj/EBG

Tool for estimating the Felsenstein bootstrap support of phylogenetic trees

Language: Python - Size: 24.1 MB - Last synced at: 11 days ago - Pushed at: 3 months ago - Stars: 6 - Forks: 2

EstevesX10/ML1-AdaBoost-Analysis-Optimization

AdaBoost Analysis and Optimization [Machine Learning I Course Project]

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prneidhardt/Ensemble-Learning

EasyVisa Project

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itsatefe/Machine-Learning

Machine Learning Algorithms

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StrangeCoder1729/FinancialFraudDetectionModels

Developed and evaluated machine learning and deep learning models for detecting financial fraud.

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jElhamm/Model-Ensembles-Boosting-In-Machine-Learning

"This repository contains implementations of Boosting method, popular techniques in Model Ensembles, aimed at improving predictive performance by combining multiple models. by using titanic database."

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katsof/probable-sniffle-NLP

Big project: NLP Keyword Extraction and Predictive models (YAKE!, KeyBERT, Naives Bayes, Boosting Gradient)

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LinggarM/Ensemble-Learning-Comparison-on-Diabetes-Classification

Comparison of ensemble learning methods on diabetes disease classification with various datasets

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kongju7/my_project1_2

Personal projects 1 & 2

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daemonX10/Diamond-Price-predication

Our model uses machine learning algorithms to predict the Price of Diamond Using Feature like Carar (size) , Color , Clarity , Cut of Diamond. For this model we have used Gradient Boosting Regressor . This is end to end project where we have trained the model and deployed , pipeline is for ingestion of data and prediction of price.

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dardenkyle/Credit-Card-Users-Churn-Prediction

Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it

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dheeraj-19/MachineLearning

Repo to store all the concepts and codes that I have learned and worked on in the Machine Learning field

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yuvalofek/py_xgboost

Python implementation of XGBoost trees

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cvogitgud/BoostedLinearClassifier

Repo for my Boosted Cluster Means Classifier

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nitinpalla/AIML

Personal projects on AI and ML

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ArtemKornev0/Classification-task-deposit-

Задача классификации. (предсказание открытия клиентом депозита в банке) / Classification task. Prediction of the client's deposit opening in the bank.

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wiegertj/BAD

Tool for estimating the difficulty of phylogenetic placements

Language: Python - Size: 4.29 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Abdul-AA/Kickstarters

Predictive Modeling and Clustering Insights for Kickstarter Success

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CodeLtDave/Boosting-Algorithms-ML-Seminararbeit

Exploration of Boosting Algorithms in Machine Learning: This repository hosts a seminar paper examining key boosting algorithms like AdaBoost, Gradient Boosting, and XGBoost. It includes theoretical insights, practical applications, and comparative analyses, providing a comprehensive understanding of boosting techniques in ML.

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NourKamaly/AirlineTicketPricePrediction

First rank winner in the Machine Learning Course Competition for class 2021-2022. Airline ticket price prediction from end to end (analysis - preprocessing - modeling - testing - deployment - documentation) between Indian cities

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bautidea/Data_Science

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hossamAhmedSalah/Machine_Learning_MSP

MSP 23 workshop of machine learning

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alifrmf/Mobile-Price-Prediction-Classification-Analysis

Supervised Machine Learning Analysis Using Classification Models

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muhammadravi251001/medical-text-classification

Code for a multi-label text classification model for medical inquiry documents using an ensemble learning approach: specifically Boosting.

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GyanPrakashkushwaha/Customer-Churn-Prediction

Customer Churn Prediction using Machine Learning and Deep learning. With Integration of MLFlow

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dagartga/Boosted-Models-for-Parkinsons-Prediction

Comparison of XGBoost, CatBoost, and LGBM for Parkinsons Classification

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vasatodorovic/ToxicityOfMolecules

Project on course "Data Mining 2"

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fjpacheco/machine-learning

Trabajos prácticos realizados en la materia Organización de Datos de la FIUBA.

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ejaj/diabetes-prediction

Diabetes prediction

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brunograssano/TP-Organizacion-de-datos

TPs de la materia Organización de Datos - Catedra Collinet - FIUBA - 2C2020

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karthik-d/SnakeCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022

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MahaThafar/DTi2Vec

This repository provides an implementation of the DTi2Vec tool, to identify Drug-Target interaction using network embedding and ensemble learning

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goz1985/RST-ARM-GLM_-Research

Work on combining Logit model with an information granulation method for better interpretability

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Yemi-Ak/Ensemble-Techniques-EasyVisa

Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

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nicoladisabato/online-shoppers-intention

Binary classification with Boosting ensemble algorithm

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amondalgit/DMML23-assignments

Data Mining Machine Learning | Assignments | JAN-APR 2023 | CMI

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Showndarya/data-science-kaggle-competition

The goal of this competition is to predict the star rating associated with user reviews from Amazon Movie Reviews using the available features (BU CAS CS 506)

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karthik-d/FungiCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

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QuyAnh2005/homemade-machine-learning

Understand and code some basic algorithms in machine learning from scratch

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shubhamsawant0601/Machine_Learning

Repository of explaination and python codes with Scikit-Learn for different ML algorithms.

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karthik-d/Boilerplate-for-Active-Learning

Templated boilerplate to perform Active Learning.

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MuhammadUsmanTipu/SVM-Boosting-DTree-Twitter-Sentiment-Analysis-on-Twitter-Dataset

What is the relationship between airline sentiments and airlines? What is the reason for the negativity mentioned in the dataset? What is the relation of time with sentiments? Which model is best for sentiment analysis when we do ensemble learning?

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lauren-alexandra/subscription-prediction

ensemble techniques

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CHYMEE/Quality-Metric-of-Global-Ecological-Footprint

Second project worked on at Hamoye Internship involving a classification problem.

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parsa-abbasi/IUST-Pattern-Recognition

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Serfati/ensamble-learning

:cyclone: Ensemble learning approch implementing cascading meta-learner

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madhur02/Ensemble_learning_on_Loan_dataset

Ensemble Learning Tutorial

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harjeet-blue/Ensemble-Learning-Bagging-and-Boosting

Ensemble is a machine learning concept in which multiple models are trained using the same learning algorithm

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RISHIKESHAVAN/ensemble-learning

Multi-classification of a cyber-bullying tweets dataset

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ligerfotis/CSE6363_Machine_Learning

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

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Ayda-Darvishan/Tuning-ML-Classifiers

The project includes building seven different machine learning classifiers (including Linear Regression, Decision Tree, Bagging, Random Forest, Gradient Boost, AdaBoost, and XGBoost) using Original, OverSampled, and Undersampled data of ReneWind case study, tuning hyperparameters of the models, performance comparisons, and pipeline development for productionizing the final model.

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Rakan-z/KCL-DS-Assignments-MSc

This repository consists of folders which include some of the courseworks I have completed in my Data Science MSc at KCL.

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OfficialNMN/Car-Price-Prediction

End to End data science project on dataset of used cars from CarDekho.

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disha2sinha/UndErNsembled Fork of SohelRaja/UndErNsembled

In this project, we reduced an imbalanced dataset to a balanced dataset using Under-sampling approach by applying Consensus Clustering using 'Simple Majority Voting' consensus function and further saw the increase in the accuracy of disease prediction by running multiple classifiers with bagging and boosting technique.

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TrilokiDA/Medication-Compliance-Forecasting

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