Question

h2o.ensemble中的错误（x = x，y = y，training_frame = train，family = family，：family = gamma需要正面响应回溯：

h2o.ensemble（x = x，y = y，training_frame = train，family = family，。 learner = learner，metalearner = metalearner，cvControl = list（V = 5，。 shuffle = TRUE））
停止（＆＃34; family = gamma需要积极响应＆＃34;）

响应＆＃34; y＆＃34;同时具有消极和正面价值。

码：

## Load required packages
library(h2o)
library(h2oEnsemble)

h2o.init(nthreads = -1, max_mem_size = "8G")

data <- h2o.importFile('./input/df_train.csv')

# Partition the data into train and test sets
splits <- h2o.splitFrame(data, seed = 1)
train <- splits[[1]]
test <- splits[[2]]

# Identify response and predictor variables
y <- "logerror"
x <- setdiff(colnames(data), c(y, "parcelid", "transactiondate"))
print(x)


# Specify the base learner library & the metalearner
learner <- c("h2o.glm.wrapper", "h2o.randomForest.wrapper", 
            "h2o.xgboost.wrapper",
            "h2o.gbm.wrapper", "h2o.deeplearning.wrapper")
metalearner <- "h2o.glm.wrapper"
family <- "gaussian"

# Train the ensemble using 5-fold CV to generate level-one data

fit <- h2o.ensemble(x = x, y = y,
                training_frame = train,
                family = family,
                learner = learner,
                metalearner = metalearner,
                cvControl = list(V = 5, shuffle = TRUE))

# Evaluate performance on a test set
perf <- h2o.ensemble_performance(fit, newdata = test)
perf

Answer 1

这是 h2oEnsemble v0.2.0中的一个错误，当我添加对额外family值（gamma，poisson等）的支持时引入了该错误。我有fixed the bug并发布了 h2oEnsemble v0.2.1;您可以找到下载新包here的链接，或使用下面的R命令：

install.packages("https://h2o-release.s3.amazonaws.com/h2o-ensemble/R/h2oEnsemble_0.2.1.tar.gz", repos = NULL)

另外，您的代码尝试使用包装器"h2o.xgboost.wrapper"来包含XGBoost模型 - h2oEnsemble 包中没有内置的XGBoost包装器，所以不会工作。我将在 h2o 3.14.0.1发布后添加XGBoost包装器。这应该发生在下一周或两周。

H2o.ensemble：family＆lt; - ＆＃34; gaussian＆＃34;，with family = gamma的错误需要肯定的响应

1 个答案: