bagging-ensemble
There are 116 repositories under bagging-ensemble topic.
Anello92/Machine_Learning_Python
Top Machine Learning Algorithms Detailed in Python and Preprocessing for Machine Learning
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.
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
Pythondeveloper6/Ensemble-learning-beginner-guide
machine learning ensemble learning types in easy steps with examples
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"
shubhamsawant0601/Machine_Learning
Repository of explaination and python codes with Scikit-Learn for different ML algorithms.
ua-datalab/MLWorkshops
UArizona DataLab Workshops
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)
VivekSagarSingh/Probability-of-Credit-card-Default
Classification problem using multiple ML Algorithms
3dot14shreyansh/random_forest_
Brief theoretical description about Random forest and application about the same.
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
ZeeshanKhalid2k01/Bagging
Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance