title: “Automated Model Development Process”

author: “Fan Dongping”

date: “2019-04-28”

output: rmarkdown::html_vignette

vignette: >

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     library(creditmodel)
     if (!dir.exists("c:/test_model")) dir.create("c:/test_model")
     setwd("c:/test_model")
     #set parameters
     LR.params = lr_params(
     bins_control = list(bins_num = 8, bins_pct = 0.05, b_chi = 0.02, b_odds = 0.1, b_psi = 0.02, b_gb = 0.15, mono = 0.3, gb_psi = 0.05, kc = 1),score_card = TRUE, cor_p = 0.7, iv_i = 0.02, psi_i = 0.1)
     XGB.params = xgb_params(nrounds = 10000, params = list(max.depth = 4, eta = 0.01, min_child_weight = 50, subsample = 0.5, colsample_bytree = 0.6, gamma = 0, max_delta_step = 1, eval_metric = "auc", objective = "binary:logistic"), early_stopping_rounds = 300)
     #training model
     Lending_model = training_model( dat_train = lendingclub, model_name = "lendingclub", target = "loan_status", occur_time = "issue_d",ex_cols = c("last_credit_pull_d", "next_pymnt_d", "prncp|recoveries|rec_|funded_amnt|pymnt|fee$"),obs_id = "id", prop = 0.7,feature_filter = list(filter = c("IV", "PSI", "COR", "XGB"), cv_folds = 1, iv_cp = 0.02,psi_cp = 0.1, cor_cp = 0.8, xgb_cp = 0, hopper = TRUE), algorithm = list("LR", "XGB"),LR.params = LR.params, XGB.params = XGB.params, parallel = FALSE,save_pmml = FALSE,  plot_show = FALSE, seed = 46)