return sigmoid(sum( (examplefor in self trees)+extra def leaf_value(selfegsdomain=[ , ])"""value at the leaves for examples egs domain argument is ignored""pred_acts [(self gtb_predictor( ),self target( )for in egsreturn sum( - for ( ,ain pred_acts/(sum( *( -pfor ( ,ain pred_acts)+self lambda_reg def sum_losses(selfdata_subset)"""returns sum of losses for dataset (assuming leaf is formed with no more splits""leaf_val self leaf_value(data_subseterror sum(evaluate log_loss(self gtb_predictor( ,leaf_val)self target( )for in data_subsetself gamma return error testing learnboosting py -(continued data data_from_file('data/carbool csv'target_index=- seed= gtb_learner gtb_learner(data gtb_learner learn(version june