[HTML][HTML] A hybrid machine learning model for classifying gene mutations in cancer using LSTM, BiLSTM, CNN, GRU, and GloVe
In our study, we introduce a novel hybrid ensemble model that synergistically combines
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …
Quantifying Overfitting: Introducing the Overfitting Index
S Aburass - arXiv preprint arXiv:2308.08682, 2023 - arxiv.org
In the rapidly evolving domain of machine learning, ensuring model generalizability remains
a quintessential challenge. Overfitting, where a model exhibits superior performance on …
a quintessential challenge. Overfitting, where a model exhibits superior performance on …
An Ensemble Approach to Question Classification: Integrating Electra Transformer, GloVe, and LSTM
This paper introduces a novel ensemble approach for question classification using state-of-
the-art models--Electra, GloVe, and LSTM. The proposed model is trained and evaluated on …
the-art models--Electra, GloVe, and LSTM. The proposed model is trained and evaluated on …
Parameter-Selective Continual Test-Time Adaptation
J Tian, F Lyu - arXiv preprint arXiv:2407.02253, 2024 - arxiv.org
Continual Test-Time Adaptation (CTTA) aims to adapt a pretrained model to ever-changing
environments during the test time under continuous domain shifts. Most existing CTTA …
environments during the test time under continuous domain shifts. Most existing CTTA …
Framework for Enhanced Digital Image Transmission Security: Integrating Hu Moments, Digital Watermarking, and Cryptographic Hashing for Integrity Verification
Image stability is very important in a time when digital image communication is essential to
many fields. Modern online dangers are often too complicated for old security methods to …
many fields. Modern online dangers are often too complicated for old security methods to …
Optimizing Customer Response Prediction in Auto Insurance: A Comparative Study of Machine Learning Models
This study examines various machine learning models to predict customer responses in the
auto insurance industry. We focus on metrics like accuracy, precision, recall, and F1-score …
auto insurance industry. We focus on metrics like accuracy, precision, recall, and F1-score …
[PDF][PDF] Systems and Soft Computing
In our study, we introduce a novel hybrid ensemble model that synergistically combines
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …
LSTM, BiLSTM, CNN, GRU, and GloVe embeddings for the classification of gene mutations …