1 line
128 KiB
JavaScript
1 line
128 KiB
JavaScript
Search.setIndex({"docnames": ["index", "modules", "quapy", "quapy.classification", "quapy.data", "quapy.method", "wiki/Datasets", "wiki/Evaluation", "wiki/ExplicitLossMinimization", "wiki/Home", "wiki/Methods", "wiki/Model-Selection", "wiki/Plotting", "wiki/Protocols"], "filenames": ["index.rst", "modules.rst", "quapy.rst", "quapy.classification.rst", "quapy.data.rst", "quapy.method.rst", "wiki/Datasets.rst", "wiki/Evaluation.rst", "wiki/ExplicitLossMinimization.rst", "wiki/Home.rst", "wiki/Methods.rst", "wiki/Model-Selection.rst", "wiki/Plotting.rst", "wiki/Protocols.rst"], "titles": ["Welcome to QuaPy\u2019s documentation!", "quapy", "quapy package", "quapy.classification package", "quapy.data package", "quapy.method package", "Datasets", "Evaluation", "Explicit Loss Minimization", "<no title>", "Quantification Methods", "Model Selection", "Plotting", "Protocols"], "terms": {"i": [0, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13], "python": [0, 4, 6], "base": [0, 1, 2, 3, 6, 10], "open": [0, 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"BayesianCC (New in v0.1.9!)": [[10, "bayesiancc-new-in-v0-1-9"]], "Expectation Maximization (EMQ)": [[10, "expectation-maximization-emq"]], "Hellinger Distance y (HDy)": [[10, "hellinger-distance-y-hdy"]], "Threshold Optimization methods": [[10, "threshold-optimization-methods"]], "Kernel Density Estimation methods (KDEy)": [[10, "kernel-density-estimation-methods-kdey"]], "Meta Models": [[10, "meta-models"]], "Ensembles": [[10, "ensembles"]], "The QuaNet neural network": [[10, "the-quanet-neural-network"]], "Model Selection": [[11, "model-selection"]], "Targeting a Quantification-oriented loss": [[11, "targeting-a-quantification-oriented-loss"]], "Targeting a Classification-oriented loss": [[11, "targeting-a-classification-oriented-loss"]], "Plotting": [[12, "plotting"]], "Diagonal Plot": [[12, "diagonal-plot"]], "Quantification bias": [[12, "quantification-bias"]], "Error by Drift": [[12, "error-by-drift"]], "Protocols": [[13, "protocols"]], "Artificial-Prevalence Protocol": [[13, "artificial-prevalence-protocol"]], "Sampling from the unit-simplex, the Uniform-Prevalence Protocol (UPP)": [[13, "sampling-from-the-unit-simplex-the-uniform-prevalence-protocol-upp"]], "Natural-Prevalence Protocol": [[13, "natural-prevalence-protocol"]], "Other protocols": [[13, "other-protocols"]]}, "indexentries": {"app (class in quapy.protocol)": [[2, "quapy.protocol.APP"]], "abstractprotocol (class in quapy.protocol)": [[2, "quapy.protocol.AbstractProtocol"]], "abstractstochasticseededprotocol (class in quapy.protocol)": [[2, "quapy.protocol.AbstractStochasticSeededProtocol"]], "artificialprevalenceprotocol (in module quapy.protocol)": [[2, "quapy.protocol.ArtificialPrevalenceProtocol"]], "configstatus (class in quapy.model_selection)": [[2, "quapy.model_selection.ConfigStatus"]], "domainmixer (class in quapy.protocol)": [[2, "quapy.protocol.DomainMixer"]], "error (quapy.model_selection.status attribute)": [[2, "quapy.model_selection.Status.ERROR"]], "earlystop (class in quapy.util)": [[2, "quapy.util.EarlyStop"]], "gridsearchq (class in quapy.model_selection)": [[2, "quapy.model_selection.GridSearchQ"]], "hellingerdistance() (in module quapy.functional)": [[2, "quapy.functional.HellingerDistance"]], "invalid (quapy.model_selection.status attribute)": [[2, "quapy.model_selection.Status.INVALID"]], "iterateprotocol (class in quapy.protocol)": [[2, "quapy.protocol.IterateProtocol"]], "npp (class in quapy.protocol)": [[2, "quapy.protocol.NPP"]], "naturalprevalenceprotocol (in module quapy.protocol)": [[2, "quapy.protocol.NaturalPrevalenceProtocol"]], "onlabelledcollectionprotocol (class in quapy.protocol)": [[2, "quapy.protocol.OnLabelledCollectionProtocol"]], "return_types (quapy.protocol.onlabelledcollectionprotocol attribute)": [[2, "quapy.protocol.OnLabelledCollectionProtocol.RETURN_TYPES"]], "success (quapy.model_selection.status attribute)": [[2, "quapy.model_selection.Status.SUCCESS"]], "status (class in quapy.model_selection)": [[2, 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