Python/H2o：从 H2ORandomForestEstimator 模型中绘制树/提取规则

Question

是否有任何“简单”的方法可以从 H2O 随机森林模型中绘制树。我也有兴趣提取结果规则？

Answer 1

是的。

从这个文档：

• http://docs.h2o.ai/h2o/latest-stable/h2o-genmodel/javadoc/overview-summary.html#viewing-a-mojo

以下代码片段展示了如何从 R 下载 MOJO 并在命令行上运行 PrintMojo 工具来制作 .png 文件：

library(h2o)
h2o.init()
df <- h2o.importFile("http://s3.amazonaws.com/h2o-public-test-data/smalldata/airlines/allyears2k_headers.zip")
model <- h2o.gbm(model_id = "model",
                 training_frame = df,
                 x = c("Year", "Month", "DayofMonth", "DayOfWeek", "UniqueCarrier"),
                 y = "IsDepDelayed",
                 max_depth = 3,
                 ntrees = 5)
h2o.download_mojo(model, getwd(), FALSE)

# Now download the latest stable h2o release from http://www.h2o.ai/download/
# and run the PrintMojo tool from the command line.
#
# (For MacOS: brew install graphviz)
# java -cp h2o.jar hex.genmodel.tools.PrintMojo --tree 0 -i model.zip -o model.gv
# dot -Tpng model.gv -o model.png
# open model.png