bagging-ensemble

alifrmf/Mobile-Price-Prediction-Classification-Analysis

Supervised Machine Learning Analysis Using Classification Models

jddeguia/bagging-lstm

Implementation of bagging-based ensemble for solar irradiance prediction. Base learners used in ensemble learning is stacked-LSTM

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'.

bupt-ai-cz/BreastCancerCNN

https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

rochitasundar/Customer-profiling-using-ML-EasyVisa

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

a3X3k/Spam-Email-Detection

itsmethahseer/clustering-and-Ensemble-techniques

Welcome to the Machine Learning Repository - Part 4! This repository focuses on unsupervised machine learning algorithms, particularly clustering techniques, and explores the fascinating world of ensemble methods, including boosting and bagging.

QuyAnh2005/homemade-machine-learning

Understand and code some basic algorithms in machine learning from scratch

Erdos1729/text-classification-ml

Application of various text classification algorithms on multiple datasets.

prneidhardt/Ensemble-Learning

EasyVisa Project

Abdulrahmankhaled11/Stroke-Prediction-Ensemble-Learning-For-Beginners

Machine Learning Application In The Medical Field Used for predicting the occurrence of stroke for the patients depends on the patient information

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.

daiphuongngo/Banking-Dataset-Imbalanced-Learn-Comparison

Banking-Dataset-Marketing-Targets

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

MoinDalvs/Assignment_Random_Forest_1

Use Random Forest to prepare a model on fraud data treating those who have taxable income <= 30000 as "Risky" and others are "Good"

Pythondeveloper6/Ensemble-learning-beginner-guide

machine learning ensemble learning types in easy steps with examples

shubhamsawant0601/Machine_Learning

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

AdiShirsath/Machine_learning_projects

Projects on Classification and Regression

Aysenuryilmazz/hr_analytics_ML

ML models for HR classification problem. For more information please visit the link: https://datahack.analyticsvidhya.com/contest/wns-analytics-hackathon-2018-1/

SimranS22/Heart-Disease-Prediction-Model-SurTech

A ML application(deployed on flask) to detect heart disease in patients based on medical features.

StrangeCoder1729/FinancialFraudDetectionModels

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

tex216/ML-Strategy-Design-for-Stock-Investment

Developed a ML assisted stock trading strategy to long or short a stock by training a random forest learner (random tree with bagging), details see the Final-Project-Report.

tien02/salary-prediction

Predicting developer's salary from Stack Overflow Annual Developer Survey (https://insights.stackoverflow.com/survey)

3dot14shreyansh/random_forest_

Brief theoretical description about Random forest and application about the same.

AlessandroDiLauro/Machine-Learning-with-Tree-Based-Models-in-Python

Decision trees are supervised learning models used for problems involving classification and regression.

AnveshaM/MachineLearning_models_using_Matlab

Stepwise Multiple Linear Regression (With Interactions) and Random Forest Regression on predicting the Productivity of the Garment Factory Workers

charanya78/melanoma-detection

A two-tier convolution neural network hybrid model for malignant melanoma prediction.

Harsha-Vardhan-Tangudu/MACHINE-LEARNING-INTRUSION-DETECTION-SYSTEM

ML project based on intrusion detection system trained dataset

karthik-d/active-learning-boilerplate

Templated boilerplate for experiments in Active and Ensemble Learning.

maryamsoftdev/All-About-Ensemble-Learning-

learning python day 14

percyance/BSECNN-code

Code of the Stacking-Enhanced Bagging Ensemble Learning for Breast Cancer Classification with CNN on ICEEM 2023

RimTouny/User-Forest-Cover-Type-Prediction

Predicting Colorado forest cover types using diverse ML models for classification. Baseline creation, feature selection, comparison, and tuning optimize accuracy in this University of Ottawa Master's Machine Learning course final project (2023).

shimolina-polina/ensembles

Ensembles of machine learning models

VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

ZeeshanKhalid2k01/Bagging

Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance