在火花中使用 H2O 创建部分依赖图?

Question

我正在尝试使用以下代码创建部分依赖图。

rf_pdp = rf_model .partial_plot(data = htest, cols = ['var1', 'var2', 'var3'], plot=True)
rf_pdp 

它运行没有错误，并为每个变量生成一个包含mean_response、stddev_response std_error_mean_response的表。但是没有情节。这是因为我在 Spark 环境中运行代码吗？

我正在运行 H2O 集群版本：3.20.0.7，在 Qubole 下使用苏打水

%pyspark
# start h2o
from pysparkling import *
import h2o
hc = H2OContext.getOrCreate(spark)
# clean up the cluster just in case
h2o.remove_all()
# import data
iris = h2o.import_file("http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv")
# convert response column to a factor
iris['class'] = iris['class'].asfactor()
# set the predictor names
predictors = iris.columns[:-1]
# split into train and validation sets
train, valid = iris.split_frame(ratios = [.8], seed = 1234)
# random forest
from h2o.estimators.random_forest import H2ORandomForestEstimator
rf_model = H2ORandomForestEstimator(
score_each_iteration=True,
score_tree_interval = 5,
max_runtime_secs = 1800,
stopping_metric = 'logloss', 
stopping_tolerance=0.001,
stopping_rounds= 3,
sample_rate = 0.7, 
col_sample_rate_per_tree = 0.7,                
ntrees=1000,
balance_classes=False,
seed=456,
nfolds=5
)
rf_model.train(x=predictors, y ='class', training_frame=train)
# plot
rf_model.plot()

Answer 1

这是绘图的解决方案

import matplotlib
import matplotlib.pyplot as plt
import io
matplotlib.use('agg')
def show(p):
img = io.StringIO()
p.savefig(img, format='svg')
img.seek(0)
print("%html <div>" + img.getvalue() + "</div>")
plt.clf()
rf_model.partial_plot(data = htest, cols = plot_varimp_df["variable"].tolist(), nbins=2, plot=True)
show(plt)