test_amacli

Prompt

def make_score_transformer( ensemble_probability,): min_logodds = math.log( (1 - SCORE_MIN_PROB) / SCORE_MIN_PROB ) max_logodds = math.log( (1 - SCORE_MAX_PROB) / SCORE_MAX_PROB ) logodds_range = ( min_logodds - max_logodds ) clipped_probability = ( "min(max(X[1], {}), {})" .format( SCORE_MIN_PROB, SCORE_MAX_PROB, ) ) # PMML round() tek argümanlı olduğu için: # round(score * 10000) / 10000 expression = ( "round(10000 * {} * " "(numpy.log((1 - {}) / {}) - {}) / {}) " "/ 10000" ).format( SCORE_MAX_VALUE, clipped_probability, clipped_probability, max_logodds, logodds_range, ) transformer = ExpressionTransformer( Expression( expression ), dtype=float, ) probability_matrix = np.column_stack( [ 1.0 - ensemble_probability, ensemble_probability, ] ) transformer.fit( probability_matrix ) # Çalışan sklearn2pmml 0.132.0 yaklaşımı. return Alias( transformer, "Ensemble_Score", prefit=True, ) Şurdaki alias return etmek yaklaşımı nerdir ve neden prefit kulanlılamlı