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Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Frontiers

An explainable and efficient deep learning framework for EEG-based diagnosis of Alzheimer's disease and frontotemporal dementia

The early and accurate diagnosis of Alzheimer's Disease and Frontotemporal Dementia remains a critical challenge, particularly with traditional machine learning models which often fail to provide ...
Scientific Research Publishing

Amin, F. and Mahmoud, M. (2022) Confusion Matrix in Binary Classification Problems: A Step-by-Step Tutorial. Journal of Engineering Research, 6, Article No. 1.

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Frontiers

Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students

1 Department of Computer Science and IT, IIS Deemed to be University, Jaipur, Rajasthan, India 2 Pokhara University, Pokhara, Nepal This study examines the prediction accuracy of ensemble machine ...
IEEE

Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals

Abstract: Background: EEG signals are extremely complex in comparison to other biomedical signals, thus require an efficient feature selection as well as classification approach. Traditional feature ...
GitHub

Add sankey style confusion matrix visualization

Confusion matrices can be displayed as a colored matrix using the ConfusionMatrixDisplay class. However color scaling is hard to interpret, and spatial cues are easier to help interpret quantities ...