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Latex format for graphs
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‎1.benchmark_functions.ipynb

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‎2.Std_Mean_on_250_tests.ipynb

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‎3.number_of_samples.ipynb

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‎4.effect_of_initialization.ipynb

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‎5.Confidence_interval.ipynb

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‎algorithms/ResponseSurfaceModeling.py

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@@ -85,7 +85,7 @@ def next_step(model:Pipeline, X:np.array,Y:np.array, lr:float=0.01, method="grad
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return X_next, X_best, Y_best
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def response_surface(fun, boundaries=[[-5,-5],[5,5]], dimension:int=2,sampling_budget:int=100, tol = 1e-8, sampling_method="box_behnken", sampling_bound=0.5,
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def response_surface(fun, boundaries=[[-5,-5],[5,5]], dimension:int=2,sampling_budget:int=100, tol = 0, sampling_method="box_behnken", sampling_bound=0.5,
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iteration_method="gradient", learning_rate=0.01, verbose=False):
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model = Pipeline([('poly', PolynomialFeatures(degree=2)),

‎algorithms/__pycache__/LatinHypercubeSampling.cpython-310.pyc

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‎algorithms/__pycache__/ResponseSurfaceModeling.cpython-310.pyc

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‎algorithms/__pycache__/ResponseSurfaceModeling.cpython-311.pyc

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‎algorithms/__pycache__/SobolSampling.cpython-310.pyc

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‎algorithms/__pycache__/__init__.cpython-310.pyc

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‎algorithms_comparison.ipynb

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‎data/Ackley001.csv

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‎data/Ackley002.csv

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