Deep learning approach for microarray cancer data classification

Deep learning approach for microarray cancer data classification

Analysis of microarray data is a highly challenging problem due to the inherent complexity in the nature of the data associated with higher dimensionality, smaller sample size, imbalanced number of classes, noisy data-structure, and higher variance of feature values. This has led to lesser classific...

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Bibliographic Details
Main Authors:	Hema Shekar Basavegowda, Guesh Dagnew
Format:	Article
Language:	English
Published:	Wiley 2019-12-01
Series:	CAAI Transactions on Intelligence Technology
Subjects:	pattern classification entropy biology computing cancer learning (artificial intelligence) principal component analysis neural net architecture minimax techniques feature extraction lab-on-a-chip deep learning approach microarray cancer data classification feature values deep feedforward method 7-layer deep neural network architecture min–max approach binary cross-entropy adaptive moment estimation dimensionality reduction technique
Online Access:	https://digital-library.theiet.org/content/journals/10.1049/trit.2019.0028

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