Corrected mistakes in the solution of ps1 q2(d)-(e)#12
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andrey-shulika wants to merge 1 commit intomaxim5:mainfrom
Open
Corrected mistakes in the solution of ps1 q2(d)-(e)#12andrey-shulika wants to merge 1 commit intomaxim5:mainfrom
andrey-shulika wants to merge 1 commit intomaxim5:mainfrom
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In part (d), the plot should use the t labels instead of the y labels. In part (e), alpha should be calculated by averaging only on V_+, not on V.
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In part (d), the plot should use the t labels instead of the y labels. The idea is to demonstrate the poor performance of the naive approach of predicting t by using just the y labels. In the summer 2020 edition of this question they wrote the instructions more clearly ("even though we only used the y(i) labels for training, use the true t(i) labels for plotting").
In part (e), alpha should be calculated by averaging only on V_+ (the part of the validation set where y=1), not on all of V. Also, the correction term for the plot should be just alpha. This corresponds to the line h(x) = alpha / 2.
Update: I looked into the implementation of
util.plot(), and noticed that it differs from the summer 2020 edition. In 2020, they apply the adjustmentcorrection = 1 + np.log(2 / alpha - 1) / model_y.theta[0]insideutil.plot(), whereas in 2018 they do not. So your original solution was correct in this case. I’ve updated the pull request accordingly.