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@@ -82,13 +82,20 @@ class ILSSurrogate(Algorithm):
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model = Lasso(alpha=1e-5)
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surrogate = WalshSurrogate(order=2, size=problem.size, model=model)
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analysis = FitterAnalysis(logfile="train_surrogate.log", problem=problem)
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-
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algo = FitterAlgo(problem=problem, surrogate=surrogate, analysis=analysis, seed=problem.seed)
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+ # dynamic number of samples based on dataset real evaluations
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+ nsamples = None
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+ with open(self.solutions_file, 'r') as f:
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+ nsamples = len(f.readlines()) - 1 # avoid header
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+
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+ training_samples = int(0.7 * nsamples) # 70% used for learning part at each iteration
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+
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print("Start fitting again the surrogate model")
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+ print(f'Using {training_samples} of {nsamples} samples for train dataset')
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for r in range(10):
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print("Iteration n°{0}: for fitting surrogate".format(r))
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- algo.run(samplefile=self.solutions_file, sample=100, step=10)
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+ algo.run(samplefile=self.solutions_file, sample=training_samples, step=10)
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joblib.dump(algo, self.surrogate_file_path)
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