Hi, I have followed the demo and example code to run a simple Random Forest model using Open Source Node in Model Studio. The code is able to run as Preprocessing node but not Supervised Learning. My gut is telling me I might miss define some required variable in order to render the Assessment, but I can not figure out why, could you help to take a look? Thanks! from sklearn.ensemble import RandomForestClassifier
import pandas as pd
X = dm_traindf.loc[:, dm_input]
y = dm_traindf[dm_dec_target]
params = {'n_estimators': 100}
dm_model = RandomForestClassifier(**params)
dm_model.fit(X, y)
fullX = dm_inputdf.loc[:, dm_input]
dm_scoreddf = pd.DataFrame(dm_model.predict_proba(fullX), columns=['P__va_d_ped_death_bin0', 'P__va_d_ped_death_bin1']) More information, the name of the target is "_va_d_ped_death_bin" and it is interval, but it only has 0 and 1 value.
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