Skip to main content

Advertisement

Figure 1 | BMC Bioinformatics

Figure 1

From: Classification of microarray data using gene networks

Figure 1

Unsupervised classification results. Performance of the unsupervised classification after changing the metric with the function φ(λ) = exp(-βλ) for different values of β (left), or with the function φ(λ) = 1(λ <λ0) with varying λ0, that is, by keeping a variable number of smallest eigenvalues (right). The red curve is obtained with the KEGG network. The black curves show the result (mean and one standard deviation interval) obtained with a random network.

Back to article page