Application for soft voting algorithm demonstration
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Updated
Jun 21, 2022 - MATLAB
Application for soft voting algorithm demonstration
98.25% accurate Breast Cancer detection - This is an Ensemble Machine learning Model utilising Pytorch and Tensorflow neural networks. Scikit voting classifier was used to create soft voting.
Intro to Machine Learning Final Project
Ensemble Modelling based verifier-like Attestation Framework designed for IoT Network Security aiding in multilabel and multiclass malware detection.
Property-based audit of voting ensemble aggregators (structural asymmetry, not demographic bias)
Intro to Machine Learning Assignment 3
Spam email classification using ensemble learning.
DGA Botnet Detection using Hybrid Late Fusion — BiLSTM + DistilBERT + XGBoost through Soft Voting
A reproduced & extended soft voting multiclass , multilevel custom-tuned ensemble to assign oxidation states in MOF.
Calibrated, monotonicity-constrained ensemble for loan approval prediction. Soft-votes Logistic Regression, Decision Tree, Random Forest and a custom PyTorch network, served through a Streamlit app. 91.9% accuracy, 0.968 ROC-AUC.
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