API Reference#

This is the class and function reference of scikit-learn. Please refer to the full user guide for further details, as the raw specifications of classes and functions may not be enough to give full guidelines on their uses. For reference on concepts repeated across the API, see glossary.

Object

Description

set_arguments

Quantifier

AggregativeQuantifier

NonAggregativeQuantifier

PWKCLF

process_inputs

absolute_error

mean_absolute_error

kullback_leibler_divergence

squared_error

mean_squared_error

normalized_absolute_error

normalized_kullback_leibler_divergence

relative_absolute_error

normalized_relative_absolute_error

Protocol

APP

NPP

CC

EMQ

FM

GAC

GPAC

PCC

PWK

ACC

MAX

MS

MS2

PACC

T50

X_method

DyS

DySsyn

HDy

SMM

SORD

Ensemble

HDx

GridSearchQ

convert_columns_to_arrays

generate_artificial_indexes

generate_artificial_prevalences

get_real_prev

load_quantifier

make_prevs

normalize_prevalence

parallel

round_protocol_df

get_measure

get_method

sqEuclidean

probsymm

topsoe

hellinger

get_scores

getHist

MoSS

ternary_search

compute_table

compute_tpr

compute_fpr

adjust_threshold