Sale!

CECS 551 Assignment 5

$30.00

Category:
5/5 - (2 votes)

CECS 551
Assignment 5
Total: 20 Points
General Instruction
ˆ Submit uncompressed file(s) in the Dropbox folder via BeachBoard (Not email).
1. (20 points) Find best hyper-parameters using GridSearchCV.
ˆ Find Assignment 5.ipynb.
ˆ The toy dataset and the network design are identical with the assignment 3.
ˆ Adam optimizer is used for the optimization, and you need to determine three
parameters, beta 1, beta 2, learning rate.
ˆ Adam optimizer is given in Figure 1. beta 1 corresponds to ρ1, beta 2 corresponds
to ρ2, learning rate corresponds to ϵ.
ˆ You are asked to complete the last part of Assignment 5.ipynb to perform a grid
search using GridSearchCV.
ˆ You need to have at least three values for each hyper-parameters.
ˆ Print out the ‘negative mean squared error’ and the corresponding hyper-parameters.
-0.046273 {’beta_1’: 0.9, ’beta_2’: 0.999, ’learning_rate’: 0.0001}
-0.003971 {’beta_1’: 0.9, ’beta_2’: 0.999, ’learning_rate’: 0.001}
-0.041319 {’beta_1’: 0.9, ’beta_2’: 0.999, ’learning_rate’: 0.01}
.
.
-0.003831 {’beta_1’: 0.8, ’beta_2’: 0.99, ’learning_rate’: 0.01}
.
.
Best: -0.003831 {’beta_1’: 0.8, ’beta_2’: 0.99, ’learning_rate’: 0.01}
Figure 1: Adam optimizer

Scroll to Top