ensemble-classifier
There are 145 repositories under ensemble-classifier topic.
alicex2020/Deep-Learning-Lie-Detection
Use machine learning models to detect lies based solely on acoustic speech information
FernandoLpz/Stacking-Blending-Voting-Ensembles
This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.
Frightera/Sample-Machine-Learning-Projects
Some example projects that was made using Tensorflow (mostly). This repository contains the projects that I've experimented-tried when I was new in Deep Learning.
indrapaul824/Coronary-Heart-Disease-Prediction
This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project
mo26-web/Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning
This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.
JingweiToo/Machine-Learning-Toolbox
This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.
kkgadiraju/SatelliteImageClassification
Pixel based classification of satellite imagery - feature generation using Orfeo Toolbox, feature selection using Learning Vector Quantization, CLassification using Decision Tree, Neural Networks, Random Forests, KNN and Naive Bayes Classifier
HarshShah1997/Video-Forgery-Detection
Detection of Object-Based Forgery in Advanced Video
IPVS-AS/pusion
Pusion (Python Universal Fusion) is a generic and flexible framework written in Python for combining multiple classifier’s decision outcomes.
gugarosa/evolutionary_ensembles
📄 Official implementation regarding the paper "Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification".
ilaydaDuratnir/python-ensemble-learning
In this project, the success results obtained from SVM, KNN and Decision Tree Classifier algorithms using the data we have created and the results obtained from the ensemble learning methods Random Forest Classifier, AdaBoost and Voting were compared.
kaushalshetty/Stacking
Multiple Model Ensembling
laxmanbalaraman/Phishing-website-prediction
Building the best machine learning model to detect phishing websites.
ahmedshahriar/Customer-Churn-Prediction
Extensive EDA of the IBM telco customer churn dataset, implemented various statistical hypotheses tests and Performed single-level Stacking Ensemble and tuned hyperparameters using Optuna.
GSukr/FashionMNIST_Image_Classification
This notebook investigates whether multiple CNN models can achieve higher classification accuracy than any individual model.
Gurudev333/Loan_Prediction_by_ensemble_machine_learning_techniques
Used ensemble methods such as boosting, voting, Bagging
secondlevel/NYCU-110-2-Natural-Language-Processing
It is the nlp task to classify empathetic dialogues datasets using RoBERTa, ERNIE-2.0 and XLNet with different preprocessing method. You can get some detailed introduction and experimental results in the link below.
alexppppp/tinyimagenet-classification-ensemble
How to Train an Ensemble of Convolutional Neural Networks for Image Classification (Article on Medium)
arasgungore/multiclass-classification-using-ensemble-learning
Two ensemble models made from ensembles of LightGBM and CNN for a multiclass classification problem.
basverkennis/Flight-Sim-Cognitive-Workload-EEG-Prediction
Predicting Workload in Virtual Flight Simulations using EEG Spectral and Connectivity Features
lisavader/plasmidEC
An ensemble of plasmid classification tools
M-e-r-c-u-r-y/Machine-Learning
Machine Learning codes
danielmuthama/DL-Classifier-Face-Verification-
Deep Learning Face Detection and Verification
mmaghajani/outlier-detection
The project is about outlier detection with different methods same as FastVOA, Kmeans, DBScan or LOF, conducted on KDD dataset.
souvikmajumder26/IEEE-ECG-Ensemble-XGBoost
👨💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.
VasilikiZarkadoula/Machine-Learning-Auth-2021
Εxercises for Machine Learning course in Faculty of Informatics of Aristotle's University of Thessaloniki
alexandrebvd/udacity-capstone-project-credit-card-fraud-prediction
Udacity capstone project | Credit card fraud prediction | Supervised Learning | Ensemble model | Data Sampling
Arjun-Siva/covid-prediction
COVID-19 Diagnosis with CNN to extract features and Ensemble ML models to predict.
fusion-jena/information-retrieval-using-multiple-LLM-and-RAG
Information Retrieval using Multiple LLMs and RAG
lazybug19/FakeAlert
A fake news detection app leveraging Ensemble ML models and NLP context-analysis to evaluate the credibility of news articles by cross-referencing claims with reliable databases.
prosperityai/ensemble-learning
The process of combining different machine Algorithms so as to decrease variance,bias in Oder to improve prediction
soheilabadifard/DynED
DynED is a novel ensemble construction and maintenance approach for data stream classification that dynamically balances the diversity and prediction accuracy of its components.
StrangeCoder1729/FinancialFraudDetectionModels
Developed and evaluated machine learning and deep learning models for detecting financial fraud.
vedranav/hierarchy-decomposition-pipeline
Hierarchy decomposition pipeline is a supervised machine learning tool that constructs random forest ensembles from data sets with hierarchical class.
fatimaAfzaal/Diabetes-Prediction-Web-App
This repository contains the code for a web-based diabetes prediction application using a machine learning model. The application is built using Flask and allows users to input various health parameters to predict the likelihood of diabetes using ensemble voting classifier.
fatimaAfzaal/Multiple-Ensemble-models-Diabetes-Prediction-Project-
This project focuses on predicting the likelihood of diabetes in individuals using ensemble machine learning models. It combines various ensemble techniques, including Random Forest, AdaBoost, Gradient Boosting, Bagging, Extra Trees, XGBoost, Voting Classifier and some others to get predictions.