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statcompute/use_wtwoe.R

Created May 8, 2019 01:42
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use_wtwoe.R
df <- readRDS("archive/accepts.rds")
head(df, 1)
# bankruptcy bad app_id tot_derog tot_tr age_oldest_tr tot_open_tr tot_rev_tr tot_rev_debt tot_rev_line rev_util bureau_score purch_price msrp
# 0 0 1001 6 7 46 NaN NaN NaN NaN 0 747 19678 17160
# down_pyt purpose loan_term loan_amt ltv tot_income used_ind weight
# 947.15 LEASE 36 18730.85 109 4800 0 4.75
### BY ITERATIVE PARTITION ###
source("wqtl_bin.R")
wqtl_bin(df, bad, tot_open_tr, weight)
# bin rule cnt freq dist mv_wt bad_freq bad_rate woe iv ks
# 00 is.na($X) 1416 5398.50 0.2323 5398.5 354 0.0656 0.2573 0.0173 6.7157
# 01 $X <= 6 2994 12050.25 0.5185 0.0 579 0.0480 -0.0722 0.0026 3.0908
# 02 $X > 6 1427 5792.00 0.2492 0.0 263 0.0454 -0.1315 0.0041 0.0000
### BY GENERALIZED BOOSTED MODEL ###
source("wgbm_bin.R")
wgbm_bin(df, bad, tot_open_tr, weight)
# bin rule cnt freq dist mv_wt bad_freq bad_rate woe iv ks
# 00 is.na($X) 1416 5398.50 0.2323 5398.5 354 0.0656 0.2573 0.0173 6.7157
# 01 $X <= 2 525 2085.00 0.0897 0.0 109 0.0523 0.0166 0.0000 6.8658
# 02 $X > 2 & $X <= 3 605 2408.75 0.1036 0.0 124 0.0515 0.0004 0.0000 6.8695
# 03 $X > 3 & $X <= 5 1319 5342.75 0.2299 0.0 246 0.0460 -0.1169 0.0030 4.3181
# 04 $X > 5 & $X <= 14 1899 7696.50 0.3312 0.0 353 0.0459 -0.1210 0.0046 0.5213
# 05 $X > 14 73 309.25 0.0133 0.0 10 0.0323 -0.4846 0.0025 0.0000
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