Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis

This section describes the proposed methodology to learn a triclustering-based classifier from three-way data, from preprocessing (including creating learning examples) to classifier performance evaluation. It further describes TCtriCluster, the proposed triclustering algorithm to mine temporally constrained triclusters. Figure 1 depicts the overall workflow.

Proposed Workflow to Learn a Triclustering-based Classifier.

In what follows, consider that a three-way dataset, D, is defined by n objects \(X = \{x_1,\ldots ,x_n\}\), m features \(Y = \{y_1,\ldots ,y_m\}\), and p contexts \(Z…