QUANTILE_RANDOM_FOREST

Syntax

QUANTILE_RANDOM_FOREST(list[,namedOptions...])

Returned object

QuantileRandomForestOperator

Example

m=QUANTILE_RANDOM_FOREST(LIST(LOGDIFF(INDPRO),LOGDIFF(PAYEMS),LOGDIFF(CPIAUCSL)))
EXTRACT(m,"slideshow")

Interpretation and limitations

The first argument is LIST(Y,X1,...). Optional settings retain the existing named-argument parser: ARG(name,value), ARG_LIST, or NAME:value. Settings are validated by the existing model class. Inspect out-of-sample behavior and avoid interpreting predictive importance as causal evidence. Conditional quantile bands describe outcomes, not coefficient confidence intervals.

Available extracts

Save the command result in a variable, then use EXTRACT(result, "key"). Availability can depend on the input form and fitted model.

• fitted
• predicted
• residuals
• oob
• oob_prediction
• ols_fitted
• ols_oos
• ols_loocv
• benchmark
• ols_summary
• ols_inference
• ols
• ols_regression
• regression
• lower
• q_lower
• median
• q50
• upper
• q_upper
• quantiles
• importance
• importance_values
• equation
• rules
• consolidate_rules
• consolidated_rules
• predictor_bar_charts
• rules_bar_chart
• bar_charts
• bar_chart
• rules_charts
• rule_charts
• regimes_bar_chart
• regimes_bar_charts
• regimes
• summary
• model
• actualvsfitted
• slideshow

In indexed patterns such as beta:n, replace n with the required index.

Learn more

Detailed guide and examples