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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma

Fig. 2

Deep belief network (DBN) with two phases: pre-training and fine-tuning. Each RBM in the pre-training phase iteratively learns lower dimensional representations of the input (gene expression microarray) one RBM at a time. These lower dimensional representations are then used as input to the next RBM. The pre-training phase learns a set of weights (W = w 1 , w 2 , and w 3 ) that is used to initialize the fine-tuning phase. The fine-tuning phase optimizes the weights by minimizing the cross-entropy error

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