I followed the video of Composing advanced models with Create ML Components.
I have created the model with
let urlParameter = URL(fileURLWithPath: "/path/to/model.pkg")
let (training, validation) = dataFrame.randomSplit(by: 0.8)
let model = try await transformer.fitted(to: DataFrame(training), validateOn: DataFrame(validation)) { event in
guard let tAccuracy = event.metrics[.trainingAccuracy] as? Double else { return }
print(tAccuracy)
}
try transformer.write(model, to: url)
print("done")
Next goal is to read the model and update it with new dataFrame
let urlCSV = URL(fileURLWithPath: "path/to/newData.csv")
var model = try transformer.read(from: urlParameters) // loading created model
let newDataFrame = try DataFrame(contentsOfCSVFile: urlCSV ) // new dataFrame with features and annotations
try await transformer.update(&model, with: newDataFrame) // I want to keep previous learned data and update the model with new
try transformer.write(model, to: urlParameters) // the model saves but the only last added dataFrame are saved. Previous one just replaced with new one
But looks like I only replace old data with new one.
**The Question ** How can add new data to model I created without losing old one ?