Train Wave Height Prediction Model

Trains a Random Forest model using ranger to predict wave height.

Usage

train_wave_model(
  data,
  target = "wave_height",
  predictors = NULL,
  train_fraction = 0.7,
  seed = 42,
  ...
)

Arguments

data

Data frame with prepared features (from prepare_wave_features)

target

Target variable name (default: "wave_height")

predictors

Character vector of predictor names (default: NULL uses standard set)

train_fraction

Fraction of data for training (default: 0.7)

seed

Random seed for reproducibility (default: 42)

...

Additional arguments passed to ranger::ranger

Value

List with model, train/test indices, and feature importance

Examples

if (FALSE) { # \dontrun{
con <- connect_duckdb()
data <- query_buoy_data(con, qc_filter = FALSE)
features <- prepare_wave_features(data)
model_result <- train_wave_model(features)
DBI::dbDisconnect(con)
} # }