Ансамбль деревьев

function predict_ensemble(trees, X)
    n_samples = size(X, 1)
    n_trees = length(trees)
    predictions = zeros(n_samples)
    
    for i in 1:n_samples
        pred_sum = 0.0
        valid_preds = 0
        for tree in trees
            pred = DecisionTree.apply_tree(tree, X[i, :])
            if !isnan(pred) && !isinf(pred)
                pred_sum += pred
                valid_preds += 1
            end
        end
        predictions[i] = valid_preds > 0 ? pred_sum / valid_preds : NaN
    end
    return predictions
end