fix base_score problem.

[JiaxiangBU]

Here is the reproducible minimal example for testing.

library(xgboost)
#> Warning: 程辑包'xgboost'是用R版本3.6.1 来建造的
library(tidyverse)
#> Registered S3 methods overwritten by 'ggplot2':
#>   method         from 
#>   [.quosures     rlang
#>   c.quosures     rlang
#>   print.quosures rlang
#> Warning: 程辑包'dplyr'是用R版本3.6.1 来建造的
train_data <- mtcars %>%
  rename(y = am)
dtrain <-
  xgb.DMatrix(data = as.matrix(train_data %>% select(-y))
              , label = train_data$y)
xgb_model <- xgb.train(
  data = dtrain,
  nround = 10,
  seed = 1,
  max_depth = 1,
  objective = "binary:logistic",
  base_score = mean(train_data$y) # fix uncalibration problem
)
pred_from_model <- predict(xgb_model, newdata = dtrain)
library(sqldf)
#> Warning: 程辑包'sqldf'是用R版本3.6.1 来建造的
#> 载入需要的程辑包：gsubfn
#> Warning: 程辑包'gsubfn'是用R版本3.6.1 来建造的
#> 载入需要的程辑包：proto
#> Warning: 程辑包'proto'是用R版本3.6.1 来建造的
#> 载入需要的程辑包：RSQLite
#> Warning: 程辑包'RSQLite'是用R版本3.6.1 来建造的
library(tidypredict)
pred_from_tidypredict <-
  tidypredict_sql(xgb_model, dbplyr::simulate_dbi()) %>%
  paste("select ", ., " from mtcars") %>%
  str_replace("LN", "log") %>% 
  sqldf() %>%
  pull
(pred_from_model - pred_from_tidypredict) %>% abs %>% mean
#> [1] 1.464673e-08

^{Created on 2019-10-20 by the reprex package (v0.3.0)}

[topepo]

Please write some test cases for this.

[topepo]

Thanks for doing this.

[github-actions]

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