磚筆記本的渲染問題:IPython.lib.display.IFrame

[SR_71]

類似的問題:https://stackoverflow.com/questions/71336374/randomforestclassifier-explainer-dashboard-output-in-da..。

實際產出——磚筆記本

預期的輸出——Jupyter筆記本

可複製的代碼示例

# pip安裝explainerdashboard

從sklearn。整體進口RandomForestClassifier

從進口ClassifierExplainer explainerdashboard explainerdashboard

從explainerdashboard。數據集進口titanic_survive feature_descriptions

X_train、y_train X_test y_test = titanic_survive ()

模型= RandomForestClassifier (n_estimators = 50, max_depth = 10)。fit (X_train y_train)

講解員= ClassifierExplainer(模型、X_test y_test,

貓=[“甲板”、“開始”),

= feature_descriptions描述,

標簽=(“沒有幸存下來”,“幸存”))

ExplainerDashboard(講解員,模式=“內聯”,

重要性= False,

model_summary = False,

= True的貢獻,

尼塔= False,

shap_dependence = False,

shap_interaction = False,

decision_trees = False) .run ()

[Abishek]

請做以下調整代碼然後你將能夠得到ExplainerDashboard。

1)在磚集群的設置環境變量

例如:

DASH_REQUEST_PATHNAME_PREFIX = / driver-proxy / o / 4080082044610008/1004 - 091920 cxkidhkx / 8888

工作區ID: 4080082044610008

Cluster-ID: 1004 - 091920 - cxkidhkx

端口號:8888

2)安裝explainerdashboard圖書館

% pip安裝explainerdashboard

3)驗證“衝刺”的示例代碼

從sklearn。整體進口RandomForestClassifier

從進口ClassifierExplainer explainerdashboard explainerdashboard

從explainerdashboard。數據集進口titanic_survive feature_descriptions

X_train、y_train X_test y_test = titanic_survive ()

模型= RandomForestClassifier (n_estimators = 50, max_depth = 10)。fit (X_train y_train)

講解員= ClassifierExplainer(模型、X_test y_test,

貓=“甲板”,“開始”,

= feature_descriptions描述,

標簽=(“沒有幸存下來”,“幸存”))

ExplainerDashboard(講解員,模式= ' ',

重要性= False,

model_summary = False,

= True的貢獻,

尼塔= False,

shap_dependence = False,

shap_interaction = False,

decision_trees = False) .run (8888)

4)儀表板URL

https://xxxxxxxx.m.eheci.com/driver proxy/o/4080082044610008/1004 - 091920 cxkidhkx/8888

[SophiaEvt]

嗨@Abishek薩勃拉曼尼亞,我經曆相同的問題,逐步嚐試您的解決方案。似乎工作,但是當我去儀表板URL隻是說‘加載…“無限期(我等了一個小時才殺死它)。我試著與你的示例代碼和我自己的隻有360條記錄的數據集。同樣的問題…任何線索可能是錯的呢?

[Abishek]

環境變量:

模型講解員:

[Abishek]

@Sophia Evtimova一旦你添加火花下的環境變量配置你會得到一個儀表板