PySurvival also displays the Base Survival function of the Simulation model: We can now see an overview of the data: x_1 generate_data(num_samples = N, num_features =4) Sim = SimulationModel( survival_distribution = 'exponential',ĭataset = sim. # 2 - Generating the dataset from a Exponential parametric model # Initializing the simulation model # 1 - Importing packages import numpy as np import pandas as pd from matplotlib import pyplot as pltįrom sklearn.model_selection import train_test_splitįrom import SimulationModelįrom _forest import ConditionalSurvivalForestModelįrom import concordance_indexįrom import integrated_brier_score So, only set to True if you encounter memory problems. Seed used by the random number generator. Permutation importance computations by Breiman et al.
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