Which is more likely to result in overfitting a model? More training data, decreased nodes in neural

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Which is more likely to result in overfitting a model? More training data, decreased nodes in neural network hidden layers, eliminating sparse features, or using a Gaussian or RBF kernel in SVM?

Which is more likely to result in overfitting a model? More training data, decreased nodes in neural network hidden layers, eliminating sparse features, or using a Gaussian or RBF kernel in SVM?

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