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sql-derivative-sensitivity-analyser_demo [2018/11/27 17:01] alisa [Running guessing advantage analysis] |
sql-derivative-sensitivity-analyser_demo [2019/06/01 15:43] alisa [Setting up data objects] |
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- | // a longer description of the norm | ||
u1 = lp 2.0 latitude longitude; | u1 = lp 2.0 latitude longitude; | ||
u2 = scaleNorm 0.2 u1; | u2 = scaleNorm 0.2 u1; | ||
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We are now ready to run the analysis. Click the blue button //Analyze//. Let us first set ε = 1 and β = 0.1. Click the green button //Run Analysis//. The most interesting value in the output that we see is the //relative error//. This can be interpreted as an upper bound on the relative distance of the noisy output from the actual output, which holds with probability 80%. There is unfortunately no strict upper bound on the additive noise, and it can potentially be infinite, though with negligible probability. Hence, we can only give a probabilistic upper bound on the noise, which is in our case hard-coded to 80%. | We are now ready to run the analysis. Click the blue button //Analyze//. Let us first set ε = 1 and β = 0.1. Click the green button //Run Analysis//. The most interesting value in the output that we see is the //relative error//. This can be interpreted as an upper bound on the relative distance of the noisy output from the actual output, which holds with probability 80%. There is unfortunately no strict upper bound on the additive noise, and it can potentially be infinite, though with negligible probability. Hence, we can only give a probabilistic upper bound on the noise, which is in our case hard-coded to 80%. | ||
- | We can now play around with the model and see how the error can be minimized. | + | We can now play around with the model and see how the error can be reduced. |
- | * Try to reduce β, e.g. try = 0.1. This does not affect security in any way, but may give smaller noise level. | + | * Try to reduce β, e.g. try β = 0.01. This does not affect security in any way, but may give smaller noise level. |
* Try to reset scalings of //Table norm// to ''1.0'', or even try larger values. The error descreases, as we now consider smaller changes in the input (which means that we lose in security). | * Try to reset scalings of //Table norm// to ''1.0'', or even try larger values. The error descreases, as we now consider smaller changes in the input (which means that we lose in security). | ||
* Try out different row sensitivity. Instead of ''rows: all ;'', try some particular row, ''rows: 0 ;'' or ''rows: 1 ;''. It can be seen that ships with higher speed have larger sensitivity and hence add more noise, since changing their locations even a little may affect the arrival time more significantly. | * Try out different row sensitivity. Instead of ''rows: all ;'', try some particular row, ''rows: 0 ;'' or ''rows: 1 ;''. It can be seen that ships with higher speed have larger sensitivity and hence add more noise, since changing their locations even a little may affect the arrival time more significantly. |