Task 2 -- Mandatory Tasks: Difference between revisions
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Created page with "Errors are an option… === 2 === Basic:<div class="figure"> File:31 0.png </div>Scaled by divison max() for every individual frequency band: File:31 1.png<div class="figure"> </div> == 3 == without preparing the data via /= std:<div class="figure"> File:31 2.png </div>with equalizing the power via /= std (obviously not the best idea in this case):<div class="figure"> File:31 3.png </div> == 4 == Phase Coherence<div class="figure"> File:31 4.png <..." |
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Basic:<div class="figure"> | Basic:<div class="figure"> | ||
[[File:31 0.png]] | [[File:31 0.png]] | ||
</div>Scaled by divison max() for every individual frequency band: | </div>Scaled by divison max() for every individual frequency band:[[File:31 1.png]]<div class="figure"> | ||
[[File:31 1.png]]<div class="figure"> | |||
</div> | </div> | ||
| Line 33: | Line 31: | ||
[[File:31 11.png]] | [[File:31 11.png]] | ||
</div>Spectral Coherence<div class="figure"> | </div>Spectral Coherence<div class="figure"> | ||
[[File: | [[File:31 8.png]] | ||
</div><div class="figure"> | </div><div class="figure"> | ||
[[File: | [[File:31 9.png]] | ||
</div> | </div> | ||
== 6 == | == 6 == | ||
'''Don’t normalize the time series!''' | |||
i.e. don’t do something like this:<syntaxhighlight lang="python">data -= data.mean(axis=1, keepdims=True) | i.e. don’t do something like this:<syntaxhighlight lang="python">data -= data.mean(axis=1, keepdims=True) | ||
data /= data.std(axis=1, keepdims=True)</syntaxhighlight>Otherwise you will not classify anything.<div class="figure"> | data /= data.std(axis=1, keepdims=True)</syntaxhighlight>Otherwise you will not classify anything.<div class="figure"> | ||
[[File: | [[File:31 12.png]] | ||
</div>Scaled by divison max() for every individual frequency band (Bad times happen):<div class="figure"> | </div>Scaled by divison max() for every individual frequency band (Bad times happen):<div class="figure"> | ||
[[File: | [[File:31 13.png]] | ||
</div> | </div> | ||
== 7 == | == 7 == | ||
'''Don’t normalize the time series!''' | |||
i.e. don’t do something like this:<syntaxhighlight lang="python">data -= data.mean(axis=1, keepdims=True) | i.e. don’t do something like this:<syntaxhighlight lang="python">data -= data.mean(axis=1, keepdims=True) | ||
data /= data.std(axis=1, keepdims=True)</syntaxhighlight>Otherwise you will not classify anything.<div class="figure"> | data /= data.std(axis=1, keepdims=True)</syntaxhighlight>Otherwise you will not classify anything.<div class="figure"> | ||
[[File: | [[File:31 14.png]] | ||
</div> | </div> | ||
Latest revision as of 13:20, 23 October 2025
Errors are an option…
2
Basic:
Scaled by divison max() for every individual frequency band:
3
without preparing the data via /= std:
with equalizing the power via /= std (obviously not the best idea in this case):
4
Phase Coherence
Spectral Coherence
5
Phase Coherence
Spectral Coherence
6
Don’t normalize the time series!
i.e. don’t do something like this:
data -= data.mean(axis=1, keepdims=True)
data /= data.std(axis=1, keepdims=True)
Otherwise you will not classify anything.
Scaled by divison max() for every individual frequency band (Bad times happen):
7
Don’t normalize the time series!
i.e. don’t do something like this:
data -= data.mean(axis=1, keepdims=True)
data /= data.std(axis=1, keepdims=True)
Otherwise you will not classify anything.
