Add error handling at model choice
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@ -22,6 +22,14 @@ def choose_model(model):
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return DecisionTreeClassifier(random_state=42)
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return DecisionTreeClassifier(random_state=42)
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elif model == "neuralnet":
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elif model == "neuralnet":
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return MLPClassifier(hidden_layer_sizes=10)
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return MLPClassifier(hidden_layer_sizes=10)
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else:
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print("Unknown model selected. The choices are: ")
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print("gnb: Gaussian Naive Bayes")
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print("svc: Linear Support Vector Classification")
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print("knn: K-neighbors")
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print("tree: Decision tree")
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print("neuralnet: MLP Classifier")
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exit()
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def predict_data(data, target, model):
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def predict_data(data, target, model):
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