## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----instancepackage, include=FALSE------------------------------------------- library(ReSurv) ## ----eval=FALSE, include=TRUE------------------------------------------------- # # input_data_0 <- data_generator( # random_seed = 1, # scenario = 0, # time_unit = 1 / 360, # years = 4, # yearly_exposure = 200 # ) # # individual_data_0 <- IndividualDataPP( # data = input_data_0, # id = NULL, # categorical_features = "claim_type", # continuous_features = "AP", # accident_period = "AP", # calendar_period = "RP", # input_time_granularity = "days", # output_time_granularity = "quarters", # years = 4 # ) # ## ----eval=FALSE, include=TRUE------------------------------------------------- # # Input data scenario Delta # # input_data3 <- data_generator( # random_seed = 1, # scenario = 3, # time_unit = 1 / 360, # years = 4, # yearly_exposure = 200 # ) # # individual_data_3 <- IndividualDataPP( # data = input_data3, # id = NULL, # categorical_features = "claim_type", # continuous_features = "AP", # accident_period = "AP", # calendar_period = "RP", # input_time_granularity = "days", # output_time_granularity = "quarters", # years = 4 # ) # ## ----eval=FALSE, include=TRUE------------------------------------------------- # # hp_scenario_alpha_xgb <- list( # params = list( # booster = "gbtree", # eta = 0.9887265, # subsample = 0.7924135 , # alpha = 10.85342, # lambda = 6.213317, # min_child_weight = 3.042204, # max_depth = 1 # ), # print_every_n = 0, # nrounds = 3000, # verbose = FALSE, # early_stopping_rounds = 500 # ) # # hp_scenario_alpha_nn <- list( # batch_size = as.integer(5000), # epochs = as.integer(5500), # num_workers = 0, # tie = 'Efron', # num_layers = 2, # num_nodes = 10, # optim = "SGD", # batch_size = as.integer(5000), # lr = 0.3023043, # xi = 0.426443, # eps = 0, # activation = "SELU", # early_stopping = TRUE, # patience = 350, # verbose = FALSE, # network_structure = NULL # ) # # hp_scenario_delta_xgb <- list(params=list(booster="gbtree", # eta=0.2717736, # subsample=0.9043068 , # alpha=7.789214, # lambda=12.09398 , # min_child_weight=22.4837 , # max_depth = 4), # print_every_n = 0, # nrounds=3000, # verbose= FALSE, # early_stopping_rounds = 500) # # hp_scenario_delta_nn <- list( # batch_size = as.integer(5000), # epochs = as.integer(5500), # num_workers = 0, # tie = 'Efron', # num_layers = 2, # num_nodes = 2, # optim = "Adam", # batch_size = as.integer(5000), # lr = 0.3542422, # xi = 0.1803953, # eps = 0, # activation = "LeakyReLU", # early_stopping = TRUE, # patience = 350, # verbose = FALSE, # network_structure = NULL # ) # ## ----eval=FALSE, include=TRUE------------------------------------------------- # # resurv_model_xgb_A <- ReSurv(individual_data_0, # hazard_model = "XGB", # hparameters = hp_scenario_alpha_xgb) # # resurv_model_nn_A <- ReSurv(individual_data_0, # hazard_model = "NN", # hparameters = hp_scenario_alpha_nn) # # resurv_model_xgb_D <- ReSurv(individual_data_3, # hazard_model = "XGB", # hparameters = hp_scenario_delta_xgb) # # resurv_model_nn_D <- ReSurv(individual_data_3, # hazard_model = "NN", # hparameters = hp_scenario_delta_nn) # # ## ----eval=FALSE, include=TRUE------------------------------------------------- # plot(resurv_model_xgb_A) ## ----eval=FALSE, include=TRUE------------------------------------------------- # plot(resurv_model_xgb_D) ## ----eval=FALSE, include=TRUE------------------------------------------------- # plot(resurv_model_nn_A, nsamples = 10000) ## ----eval=FALSE, include=TRUE------------------------------------------------- # plot(resurv_model_nn_D, nsamples=10000)