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import numpy as np import pandas as pd def Outputs(data): return np.round(1.-(1./(1.+np.exp(-data)))) def GeneticFunction(data): return ((np.minimum( ((((0.058823499828577 + data[“Sex”]) – np.cos((data[“Pclass”] / 2.0))) * 2.0)), ((0.885868))) * 2.0) + np.maximum( ((data[“SibSp”] – 2.409090042114258)), ( -(np.minimum( (data[“Sex”]), (np.sin(data[“Parch”]))) * data[“Pclass”]))) + (0.138462007045746 * ((np.minimum( (data[“Sex”]), (((data[“Parch”] / 2.0) / 2.0))) * data[“Age”]) – data[“Cabin”])) + np.minimum( ((np.sin((data[“Parch”] * ((data[“Fare”] – 0.720430016517639) * 2.0))) * 2.0)), ((data[“SibSp”] / 2.0))) + np.maximum( (np.minimum( ( -np.cos(data[“Embarked”])), (0.138462007045746))), (np.sin(((data[“Cabin”] – data[“Fare”]) * 2.0)))) + -np.minimum( ((((data[“Age”] * data[“Parch”]) * data[“Embarked”]) + data[“Parch”])), (np.sin(data[“Pclass”]))) + np.minimum( (data[“Sex”]), ((np.sin( -(data[“Fare”] * np.cos((data[“Fare”] * 1.630429983139038)))) / 2.0))) + np.minimum( ((0.230145)), (np.sin(np.minimum( (((67.0 / 2.0) * np.sin(data[“Fare”]))), (0.31830988618379069))))) + np.sin((np.sin(data[“Cabin”]) * (np.sin((12.6275)) * np.maximum( (data[“Age”]), (data[“Fare”]))))) + np.sin(((np.minimum( (data[“Fare”]), ((data[“Cabin”] * data[“Embarked”]))) / 2.0) * -data[“Fare”])) + np.minimum( (((2.675679922103882…


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