QUESTION: 93

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a machine learning specialist will build a binary classifier based on two features: age of account, denoted by x, and transaction month, denoted by y. The class distributions are illustrated in the provided figure. The positive class is portrayed in red, while the negative class is portrayed in black.

Which model would have the HIGHEST accuracy?

Linear support vector machine (SVM)
Decision tree
Support vector machine (SVM) with a radial basis function kernel
Single perceptron with a Tanh activation function

Answer(s): C

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QUESTION: 94

A health care company is planning to use neural networks to classify their X-ray images into normal and abnormal classes. The labeled data is divided into a training set of 1,000 images and a test set of 200 images. The initial training of a neural network model with 50 hidden layers yielded 99% accuracy on the training set, but only 55% accuracy on the test set.

What changes should the Specialist consider to solve this issue? (Choose three.)

Choose a higher number of layers
Choose a lower number of layers
Choose a smaller learning rate
Enable dropout
Include all the images from the test set in the training set
Enable early stopping

Answer(s): B,D,F

Reference:

https://www.kdnuggets.com/2019/12/5-techniques-prevent-overfitting-neural-networks.html

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QUESTION: 95

This graph shows the training and validation loss against the epochs for a neural network.

The network being trained is as follows:
•Two dense layers, one output neuron
•100 neurons in each layer
•100 epochs
•Random initialization of weights

Which technique can be used to improve model performance in terms of accuracy in the validation set?

Early stopping
Random initialization of weights with appropriate seed
Increasing the number of epochs
Adding another layer with the 100 neurons

Answer(s): A

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QUESTION: 96

A Machine Learning Specialist is attempting to build a linear regression model.

Given the displayed residual plot only, what is the MOST likely problem with the model?

Linear regression is inappropriate. The residuals do not have constant variance.
Linear regression is inappropriate. The underlying data has outliers.
Linear regression is appropriate. The residuals have a zero mean.
Linear regression is appropriate. The residuals have constant variance.

Answer(s): A

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Free AWS Certified Machine Learning - Specialty Exam Braindumps (page: 24)

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QUESTION: 96