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mlquantify 0.1.1 documentation

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  • mlquantify
    • set_arguments
  • mlquantify.base
    • Quantifier
    • AggregativeQuantifier
    • NonAggregativeQuantifier
  • mlquantify.classification.methods
    • PWKCLF
  • mlquantify.evaluation.measures
    • 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
  • mlquantify.evaluation.protocol
    • Protocol
    • APP
    • NPP
  • mlquantify.methods.aggregative
    • CC
    • EMQ
    • FM
    • GAC
    • GPAC
    • PCC
    • PWK
    • ACC
    • MAX
    • MS
    • MS2
    • PACC
    • T50
    • X_method
    • DyS
    • DySsyn
    • HDy
    • SMM
    • SORD
  • mlquantify.methods.meta
    • Ensemble
  • mlquantify.methods.non_aggregative
    • HDx
  • mlquantify.model_selection
    • GridSearchQ
  • mlquantify.utils.general
    • 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
  • mlquantify.utils.method
    • sqEuclidean
    • probsymm
    • topsoe
    • hellinger
    • get_scores
    • getHist
    • MoSS
    • ternary_search
    • compute_table
    • compute_tpr
    • compute_fpr
    • adjust_threshold
  • API Reference
  • mlquantify.base

mlquantify.base#

Quantifier

Base class for all quantifiers, it defines the basic structure of a quantifier.

AggregativeQuantifier

A base class for aggregative quantifiers.

NonAggregativeQuantifier

Abstract base class for non-aggregative quantifiers.

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Quantifier