An artificial Neural Network & An Ensemble Model - IT Assignment Help

Assignment Task     

Answer the following statements with false/true.
(a) An artificial neural network can be seen as an ensemble model.
(b) A nonlinear classifier always produces a nonlinear decision boundary.
(c) Regularization can be used to avoid overfitting in a linear regression model.
(d) You want to build a machine learning model to predicit the number of clicks on a web page button. Since the this value is an integer the problem is best viewed as a classification problem.
(e) Deep learning can be regarded as a parametric method.

(f) Regularization must be only used for regression models and not for classifi- cation models.

(g) In an artificial neural network, a tanh activation function is preferable to a ReLU activation function as it takes care of vanishing gradients.
(h) In ANNs, the main point of using Dropout in the architecture is to reduce the training error on a given dataset.

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