Resolution:
standard / ## Figure 5.
Model accuracy as a function of modeling method and data size. The figure shows the effects of using different sizes of data sets for fitting the
models and the effects on the model accuracy as measured by the mean square error
of prediction. The mean square error of predicted data using four different methods
and using 10, 20, 40, 80, 160, and 320 data points, for both A549 and AG02603 cells
are displayed. The four methods are two linear regression methods and two neural network
methods. The linear regression methods include one that uses pairwise products of
concentrations and quadratic terms of the concentrations (QRF), and the other uses
the n-wise products of concentrations of drugs as interaction terms (LR). The two
neural network methods are a cascaded neural network with two single-neuron layers,
and a four-neuron single-layer multi-layer perceptron (MLP). As the number of points
used to generate the model increases, the mean square error decreases.
Al-Shyoukh |