Hi All,
I tried to use xgboost to model and predict count data. The predictions are
however not as expected as shown below.
# sponge count data in library(spm)
library(spm)
data(sponge)
data(sponge.grid)
names(sponge)
[1] "easting" "northing" "sponge" "tpi3" "var7" "entro7" "bs34"
"bs11"
names(sponge.grid)
[1] "easting" "northing" "tpi3" "var7" "entro7" "bs34" "bs11"
range(sponge[, c(3)])
[1] 1 39 # count sample data
# the expected predictions are:
set.seed(1234)
gbmpred1 <- gbmpred(sponge[, -c(3)], sponge[, 3], sponge.grid[, c(1:2)],
sponge.grid, family = "poisson", n.cores=2)
range(gbmpred1$Predictions)
[1] 10.04643 31.39230 # the expected predictions
# Here are results from xgboost
# use count:poisson
library(xgboost)
xgbst2.1 <- xgboost(data = as.matrix(sponge[, -c(3)]), label = sponge[, 3],
max_depth = 2, eta = 0.001, nthread = 6, nrounds = 3000, objective =
"count:poisson")
xgbstpred2 <- predict(xgbst2.1, as.matrix(sponge.grid))
head(xgbstpred2)
range(xgbstpred2)
[1] 1.109032 4.083049 # much lower than expected
table(xgbstpred2)
1.10903215408325 1.26556181907654 3.578040599823
4.08304929733276 # only four predictions, why?
36535 2714 40930 15351
plot(gbmpred1$Predictions, xgbstpred2)
# use reg:linear
xgbst2.2 <- xgboost(data = as.matrix(sponge[, -c(3)]), label = sponge[, 3],
max_depth = 2, eta = 0.001, nthread = 6, nrounds = 3000, objective =
"reg:linear")
xgbstpred2.2 <- predict(xgbst2.2, as.matrix(sponge.grid))
head(xgbstpred2.2)
table(xgbstpred2.2)
range( xgbstpred2.2)
[1] 9.019174 23.060669 # this is much closer to but still lower than what
expected
plot(gbmpred1$Predictions, xgbstpred2.2)
# use count:poisson and subsample = 0.5
set.seed(1234)
param <- list(max_depth = 2, eta = 0.001, gamma = 0.001, subsample = 0.5,
silent = 1, nthread = 6, objective = "count:poisson")
xgbst2.4 <- xgboost(data = as.matrix(sponge[, -c(3)]), label = sponge[, 3],
params = param, nrounds = 3000)
xgbstpred2.4 <- predict(xgbst2.4, as.matrix(sponge.grid))
head(xgbstpred2.4)
table(xgbstpred2.4)
range(xgbstpred2.4)
[1] 1.188561 3.986767 # this is much lower than what expected
plot(gbmpred1$Predictions, xgbstpred2.4)
plot(xgbstpred2.2, xgbstpred2.4)
All these were run in R 3.3.3 on Windows"
> Sys.info()
sysname release
"Windows" "7 x64"
version
"build 7601, Service Pack 1"
machine
"x86-64"
Have I miss-specified or missed some parameters? Or there is a bug in xgboost.
I am grateful for any help.
Kind regards,
Jin
Jin Li, PhD | Spatial Modeller / Computational Statistician
National Earth and Marine Observations | Environmental Geoscience Division
t: +61 2 6249 9899 www.ga.gov.au<http://www.ga.gov.au/>
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