pub fn train_grid(
		&mut self,
		kill_chip: &KillChip,
		handle_progress_event: &mut dyn FnMut(ProgressEvent),
	) -> Result<Vec<TrainGridItemOutput>> {
		let (table_train, table_comparison, _) = self.dataset.split();
		let grid = &self.grid;
		let comparison_metric = self.comparison_metric;
		let train_grid_item_outputs = grid
			.iter()
			.cloned()
			.enumerate()
			.take_while(|_| !kill_chip.is_activated())
			.map(|(grid_item_index, grid_item)| {
				train_grid_item(
					grid.len(),
					grid_item_index,
					grid_item,
					&table_train,
					&table_comparison,
					comparison_metric,
					kill_chip,
					handle_progress_event,
				)
			})
			.collect();
		Ok(train_grid_item_outputs)
	}
/// Train each model in the grid and compute comparison metrics.
Train each model in the grid and compute comparison metrics.
Train each model in the grid and compute comparison metrics .
pub fn train_grid(
		&mut self,
		kill_chip: &KillChip,
		handle_progress_event: &mut dyn FnMut(ProgressEvent),
	) -> Result<Vec<TrainGridItemOutput>> {
		let (table_train, table_comparison, _) = self.dataset.split();
		let grid = &self.grid;
		let comparison_metric = self.comparison_metric;
		let train_grid_item_outputs = grid
			.iter()
			.cloned()
			.enumerate()
			.take_while(|_| !kill_chip.is_activated())
			.map(|(grid_item_index, grid_item)| {
				train_grid_item(
					grid.len(),
					grid_item_index,
					grid_item,
					&table_train,
					&table_comparison,
					comparison_metric,
					kill_chip,
					handle_progress_event,
				)
			})
			.collect();
		Ok(train_grid_item_outputs)
	}
pub fn train_grid ( & mut self , kill_chip : & KillChip , handle_progress_event : & mut dyn FnMut ( ProgressEvent ) , ) -> Result < Vec < TrainGridItemOutput > > { let ( table_train , table_comparison , _ ) = self . dataset . split ( ) ; let grid = & self . grid ; let comparison_metric = self . comparison_metric ; let train_grid_item_outputs = grid . iter ( ) . cloned ( ) . enumerate ( ) . take_while ( | _ | ! kill_chip . is_activated ( ) ) . map ( | ( grid_item_index , grid_item ) | { train_grid_item ( grid . len ( ) , grid_item_index , grid_item , & table_train , & table_comparison , comparison_metric , kill_chip , handle_progress_event , ) } ) . collect ( ) ; Ok ( train_grid_item_outputs ) }
Train each model in the grid and compute comparison metrics.
Train each model in the grid and compute comparison metrics .
&mut self
kill_chip
&KillChip
handle_progress_event
&mut dyn FnMut(ProgressEvent)