Returns the predicted target using the Random Forest modeling (a way of training an ensemble of decision trees).
Predict using a stored training model.
rforest [size=INT] model=MODEL
Predict using a model trained based on subquery results.
rforest [size=INT] target=TARGET_FILED FIELD, ... [ SUBQUERY ]
- Fields as predictor variables for the Random Forest modeling.
- Name of the Random Forest model. You can generate and train the Random Forest model by connecting to the Logpresso engine via CLI.
- Field as a target variable for the Random Forest modeling.
[ SUBQUERY ]
- Subquery that returns the data set for model training.
- Number of trees within the random forest (default: 100)
This command returns the predicted value of the
target field into the _guess field.
Predict using the
# Download: https://raw.githubusercontent.com/logpresso/dataset/main/titanic/train.csv table titanic_test | rforest model=rforest_titanic | eval _guess = if(_guess=="0", "사망 ", "생존")
Predict using a model trained based on the training data set returned from a subquery.
table titanic_test | rforest target=Survived Pclass, Sex, Age, Fare, Embarked [ csvfile /test/train.csv | eval Age=double(Age), Fare=double(Fare), CanbinLetter=nvl(substr(Cabin, 0, 1), "--"), TicketType=if(isnull(long(Ticket)), substr (Ticket, 0, indexof(Ticket, " ")), "--") | rex field=Name ", (?<Title>[^.]+)" | eval Survived = if(Survived=="0", " 사망 ", "생존") ]