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Module 6 Review

Nick Feldman 14 preguntas

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Preguntas del test (14)

  1. 1 Which of the following is a correct validation fit statistic when predicting Decisions?
    1. AAll the above
    2. BAverage Profit
    3. CKolmogorov-Smirnov Statistic
    4. DMisclassification
  2. 2 Among multiple neural network model, __________ (validation fit statistic) value should be ____________.
    1. AAverage Squared Error, smallest
    2. BMisclassification, largest
    3. CLog-Likelihood, smallest
    4. DGini Coefficient, smallest
  3. 3What are some of the ways to improve the Default Neural Net Model?
    1. AChanging the architect of the network
    2. BChanging the output variables
    3. CChanging type of Neural Net(NN) from RBF to MLP
    4. DAlways keep the number of hidden layers low
  4. 4Which of the following are true about RBF(Radial Basis Functions)?
    1. ATransfer function in RBF is typically Gaussian(bell-shaped)
    2. BThe nodes input is a non-linear function of how close the hidden layer is to the target.
    3. CRadial means all inputs that are different distance from the node’s position that produce different output.
    4. DUnlike MLP, there are usually weights between input and output layer. Instead, this layer has RBF node’s position, width and height
  5. 5 In RBF Neural Network the weights will be applied between?
    1. AHidden layer and output layer
    2. BInput layer and hidden layer
    3. CCan be applied anywhere between input layer and output layer
    4. DNo weights are applied
  6. 6Which one is the transfer function typically used in RBF?
    1. AGaussian
    2. BUnit step (threshold
    3. CSigmoid
    4. DPiecewise linear
  7. 7Which of the following is a correct validation fit statistic when predicting estimates?
    1. AAverage Squared Error
    2. BROC Index
    3. CKolmogorov-Smirnov Statistic
    4. DMisclassification
  8. 8Based on the ROC Index, which model would be considered a strong one?
    1. AGreater than 0.7
    2. BGreater than 1
    3. CLess than 0.6
    4. DBetween 0.6 and 0.7
  9. 9In a neural network model, what changes to the input variables improves the model performance?
    1. ACombining or re- coding different levels in a categorical variable
    2. BAdding additional variables without a variable selection step
    3. CUsing interval variable without transformation even if the data is skewed
    4. DRemoving combination of existing variables
  10. 10When additional nodes are added to a Neural Network with Radial Basis Function, what shape does the response surface takes in?
    1. AAny shape
    2. BBell Shape
    3. CElliptical shape
    4. DSpherical shape

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Test sobre Module 6 Review, creado por Nick Feldman el 01/05/2022.
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