Exemplos de evaluate_model em Python

Exemplo n.º 1

def run(dataset, params, resultdir=".", use_params=True):
    pipeline_parameters = {}
    if use_params:
        pipeline_parameters[GaussianNB] = params

    pipeline_components = [RobustScaler, GaussianNB]
    return evaluate_model(dataset, pipeline_components, pipeline_parameters, resultdir=resultdir)

Exemplo n.º 2

def run(dataset, params, resultdir=".", use_params=True):
    pipeline_parameters = {}
    if use_params:
        pipeline_parameters[MultinomialNB] = params

    pipeline_components = [MinMaxScaler, MultinomialNB]
    return evaluate_model(dataset, pipeline_components, pipeline_parameters, resultdir=resultdir)

Exemplo n.º 3

Arquivo: PassiveAggressiveClassifier.py Projeto: sgpthomas/sklearn-pmlb-benchmarks

def run(dataset, params, resultdir=".", use_params=True):
    pipeline_parameters = {}
    if use_params:
        pipeline_parameters[PassiveAggressiveClassifier] = params

    pipeline_components = [RobustScaler, PassiveAggressiveClassifier]
    return evaluate_model(dataset,
                          pipeline_components,
                          pipeline_parameters,
                          resultdir=resultdir)

Exemplo n.º 4

Arquivo: LogisticRegression.py Projeto: sgpthomas/sklearn-pmlb-benchmarks

def run(dataset, params, resultdir=".", use_params=True):
    pipeline_parameters = {}
    if use_params:
        pipeline_parameters[LogisticRegression] = params

    pipeline_components = [RobustScaler, LogisticRegression]
    return evaluate_model(dataset,
                          pipeline_components,
                          pipeline_parameters,
                          resultdir=resultdir)