dtreevizによる可視化によるエラーを解決したい

Question

from sklearn.ensemble import RandomForestRegressor 
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.metrics import r2_score

#データの読み込み＆表示
df = pd.read_csv("study.csv", encoding="utf-8")
df = df.fillna(df.mean())
df = df.drop("data", axis=1)
df

#yを目的変数、xを説明変数として指定
y = df.loc[:,"water_temperature"]
x = df.loc[:,["airtemperature","precipitation","surface_pressure","u_component_of_wind_10m","water_level"]]

#x、yを学習用、評価用に8:2で分割
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.2, train_size = 0.8, shuffle = True)

#学習、評価
rf = RandomForestRegressor()
rf.fit(x_train, y_train)
y_pred = rf.predict(x_test)
print("正解率＝", r2_score(y_test, y_pred))

#RandomForestRegressorの可視化
from dtreeviz.trees import dtreeviz
viz = dtreeviz(
    rf,
    x,
    y,
    feature_names = x.columns.values,
    target_name = 'water_temperature'
)
display(viz)

上記のようにRandomForestRegressorで学習、評価を終えたあとdtreevizを使用して可視化を試みているのですがエラーが出てしまいます。
どの部分を修正したらよいか教えていただけないでしょうか。
エラーは下記に記載してあります。

AttributeError                            Traceback (most recent call last)
<ipython-input-60-0375a6f638be> in <module>
     13     y,
     14     feature_names = x.columns.values,
---> 15     target_name = 'water_temperature'
     16 )
     17 display(viz)

~\anaconda3\lib\site-packages\dtreeviz\trees.py in dtreeviz(tree_model, x_data, y_data, feature_names, target_name, class_names, tree_index, precision, orientation, instance_orientation, show_root_edge_labels, show_node_labels, show_just_path, fancy, histtype, highlight_path, X, max_X_features_LR, max_X_features_TD, label_fontsize, ticks_fontsize, fontname, colors, scale)
    752         highlight_path = [n.id for n in path]
    753 
--> 754     n_classes = shadow_tree.nclasses()
    755     color_values = colors['classes'][n_classes]
    756 

AttributeError: 'NoneType' object has no attribute 'nclasses'