sql-derivative-sensitivity-analyser_demo
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sql-derivative-sensitivity-analyser_demo [2018/11/27 17:01] alisa [Running sensitivity analysis] |
sql-derivative-sensitivity-analyser_demo [2019/01/09 14:41] alisa [Running sensitivity analysis] |
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| We can now play around with the model and see how the error can be reduced. | 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. | ||
sql-derivative-sensitivity-analyser_demo.txt · Last modified: 2021/06/14 11:22 by alisa
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