But Mr. Jebara says that when it has the data, the model works well.
Using imbalanced data, the model achieved AUC = 0.87 but very poor precision-recall curve (PRC) of 0.57.
For binned data, the model values at the left side of the bin are used in the fitting.
Based on the experimental data, the model is verified and the parameters are identified.
When registered with the microstructure data, the model serves to organize and index the microstructure data.
Compared the numerical results with measured experimental data, the model simulation is proved with success.
A good agreement between the experimental data the model predictions was found for the system investigated.
With two reaction rate coefficients fitted to the data, the model described Se volatilization very well.
The background data, the model assigned to the background, and the fit of the model to the background can be visualized with plot_bkg, plot_bkg_model, and plot_bkg_fit, respectively.
From these data, the model will generate maps showing factors like estimated prevalence of various poverty rates or populations of children or women at risk of malnutrition.
Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS.
