# Machine Learning and ELM

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-learning-and-elm/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the theory, applications, and advancements in Extreme Learning Machines (ELM), a machine learning framework based on feedforward neural networks with random hidden nodes. The papers cover topics such as incremental learning, classification, regression, ensemble methods, kernel-based models, and their applications in various domains. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12676 |
| Works | 79 |

## Topic papers all

Showing 15 of 79.

- [Selecting critical features for data classification based on machine learning methods](https://scholariq.org/papers/selecting-critical-features-for-data-classification-based-on-machine-learning/)
- [A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification](https://scholariq.org/papers/a-hybrid-feature-extraction-method-with-regularized-extreme-learning-machine-for/)
- [Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists](https://scholariq.org/papers/multimodal-brain-tumor-classification-using-deep-learning-and-robust-feature/)
- [A Hybrid Deep Learning-Based Approach for Brain Tumor Classification](https://scholariq.org/papers/a-hybrid-deep-learning-based-approach-for-brain-tumor-classification/)
- [Deep Transfer Learning Approaches in Performance Analysis of Brain Tumor Classification Using MRI Images](https://scholariq.org/papers/deep-transfer-learning-approaches-in-performance-analysis-of-brain-tumor/)
- [A decision support system for multimodal brain tumor classification using deep learning](https://scholariq.org/papers/a-decision-support-system-for-multimodal-brain-tumor-classification-using-deep/)
- [Multilayer feedforward networks with a nonpolynomial activation function can approximate any function](https://scholariq.org/papers/multilayer-feedforward-networks-with-a-nonpolynomial-activation-function-can/)
- [Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy](https://scholariq.org/papers/evolving-an-optimal-kernel-extreme-learning-machine-by-using-an-enhanced-grey/)
- [Classification of Brain Tumor from Magnetic Resonance Imaging Using Vision Transformers Ensembling](https://scholariq.org/papers/classification-of-brain-tumor-from-magnetic-resonance-imaging-using-vision/)
- [Brain Tumor Classification via Statistical Features and Back-Propagation Neural Network](https://scholariq.org/papers/brain-tumor-classification-via-statistical-features-and-back-propagation-neural/)
- [Classification of TrashNet Dataset Based on Deep Learning Models](https://scholariq.org/papers/classification-of-trashnet-dataset-based-on-deep-learning-models/)
- [An improved cuckoo search based extreme learning machine for medical data classification](https://scholariq.org/papers/an-improved-cuckoo-search-based-extreme-learning-machine-for-medical-data/)
- [Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine](https://scholariq.org/papers/cloud-computing-based-framework-for-breast-cancer-diagnosis-using-extreme/)
- [Online sequential extreme learning machine with forgetting mechanism](https://scholariq.org/papers/online-sequential-extreme-learning-machine-with-forgetting-mechanism/)
- [Deep Extreme Learning Machine and Its Application in EEG Classification](https://scholariq.org/papers/deep-extreme-learning-machine-and-its-application-in-eeg-classification/)

## Topic primary papers

Showing 15 of 21.

- [A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification](https://scholariq.org/papers/a-hybrid-feature-extraction-method-with-regularized-extreme-learning-machine-for/)
- [Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy](https://scholariq.org/papers/evolving-an-optimal-kernel-extreme-learning-machine-by-using-an-enhanced-grey/)
- [An improved cuckoo search based extreme learning machine for medical data classification](https://scholariq.org/papers/an-improved-cuckoo-search-based-extreme-learning-machine-for-medical-data/)
- [Cloud Computing-Based Framework for Breast Cancer Diagnosis Using Extreme Learning Machine](https://scholariq.org/papers/cloud-computing-based-framework-for-breast-cancer-diagnosis-using-extreme/)
- [Online sequential extreme learning machine with forgetting mechanism](https://scholariq.org/papers/online-sequential-extreme-learning-machine-with-forgetting-mechanism/)
- [Deep Extreme Learning Machine and Its Application in EEG Classification](https://scholariq.org/papers/deep-extreme-learning-machine-and-its-application-in-eeg-classification/)
- [Leukocyte image segmentation by visual attention and extreme learning machine](https://scholariq.org/papers/leukocyte-image-segmentation-by-visual-attention-and-extreme-learning-machine/)
- [Unsupervised extreme learning machine with representational features](https://scholariq.org/papers/unsupervised-extreme-learning-machine-with-representational-features/)
- [Incremental extreme learning machine based on deep feature embedded](https://scholariq.org/papers/incremental-extreme-learning-machine-based-on-deep-feature-embedded/)
- [Feedforward Neural Networks with a Hidden Layer Regularization Method](https://scholariq.org/papers/feedforward-neural-networks-with-a-hidden-layer-regularization-method/)
- [Calibration and decoupling of multi-axis robotic Force/Moment sensors](https://scholariq.org/papers/calibration-and-decoupling-of-multi-axis-robotic-force-moment-sensors/)
- [A Feature Selection Based on Improved Artificial Hummingbird Algorithm Using Random Opposition-Based Learning for Solving Waste Classification Problem](https://scholariq.org/papers/a-feature-selection-based-on-improved-artificial-hummingbird-algorithm-using/)
- [A hybrid-extreme learning machine based ensemble method for online dynamic security assessment of power systems](https://scholariq.org/papers/a-hybrid-extreme-learning-machine-based-ensemble-method-for-online-dynamic/)
- [A deep residual compensation extreme learning machine and applications](https://scholariq.org/papers/a-deep-residual-compensation-extreme-learning-machine-and-applications/)
- [H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification](https://scholariq.org/papers/h-qnn-a-hybrid-quantum-classical-neural-network-for-improved-binary-image/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.