Matrix Factorization-Based Prediction of Novel Drug Indications by Integrating Genomic Space

<div>The AUC results of models based on different penalization and learning rate. (a) Learning rate remains the same, while penalization coefficients increase twofold each time. (b) Penalization coefficient remains the same, while learning rate increases twofold each time.</div>

Computational and Mathematical Methods in Medicine

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Figure 2

Figure 2: Matrix Factorization-Based Prediction of Novel Drug Indications by Integrating Genomic Space 