Exemple #1
0
def main():
    fitter = fit.downscale.FitterMultiSeries()
    data = dataset.Wales5Training()
    seed = random.SeedSequence(336116686577838597869553922167649360230)
    Pool = multiprocess.Pool
    wrapper.downscale_fit(fitter, data, seed, Pool)
def main():
    fitter = fit.downscale.FitterDownscale()
    data = dataset.Wales5Training()
    seed = random.SeedSequence(135973542338678598285681473918294488781)
    Pool = multiprocess.Pool
    wrapper.downscale_fit(fitter, data, seed, Pool)
def main():
    fitter = fit.downscale.FitterDownscaleDeepGp()
    data = dataset.IsleOfManTraining()
    seed = random.SeedSequence(335181766240425557327571375931666354614)
    Pool = multiprocess.Pool
    wrapper.downscale_fit(fitter, data, seed, Pool)
Exemple #4
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def main():
    fitter = fit.downscale.FitterDownscale()
    data = dataset.IsleOfManTraining()
    seed = random.SeedSequence(41597761383904719560264433323691455830)
    Pool = multiprocess.Pool
    wrapper.downscale_fit(fitter, data, seed, Pool)
Exemple #5
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def main():
    fitter = fit.downscale.FitterMultiSeries()
    data = dataset.IsleOfManTraining()
    seed = random.SeedSequence(275033816910622348579815457010957489899)
    Pool = multiprocess.Pool
    wrapper.downscale_fit(fitter, data, seed, Pool)