Timeline for How to identify models as linear or non-linear?
Current License: CC BY-SA 4.0
9 events
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| Mar 31, 2020 at 19:51 | comment | added | tdMJN6B2JtUe | Since writing the above, I have decided that most machine learning models are non-linear because the activation functions, even if invertible, occur at the neuron or layer level of the model, rather than just at the output layer. Also, for any of you who are interested, I posted a link to this discussion on SO hoping to convince some of them to join CV: stackoverflow.com/a/60958735/12763497 | |
| Mar 30, 2020 at 16:19 | history | edited | tdMJN6B2JtUe | CC BY-SA 4.0 |
Added example of real numbers as scalars and clarified that the noise distribution must be described in terms of linear combinations, not written as a linear combination.
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| Mar 30, 2020 at 16:06 | history | edited | tdMJN6B2JtUe | CC BY-SA 4.0 |
clarified mapping of predictors to vectors and scalars to parameters.
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| Mar 30, 2020 at 12:51 | comment | added | tdMJN6B2JtUe | @whuber in my answer I wrote noise (error). Please give more focused feedback on how I failed to define noise. Because all models are wrong, there will always be error; because some are useful, sometimes we can call that error "noise" (twisted version of quotesjournal.blogspot.com/2008/12/…). | |
| Mar 21, 2020 at 12:28 | comment | added | whuber♦ | By focusing solely on the "noise" (which you don't define), your answer seems overly restrictive and somewhat at odds with what many people consider linear models, as described (inter alia) in my post at stats.stackexchange.com/a/148713/919. | |
| Mar 20, 2020 at 21:15 | review | Late answers | |||
| Mar 20, 2020 at 21:31 | |||||
| Mar 20, 2020 at 21:01 | comment | added | tdMJN6B2JtUe | Also, please note that the statistical distribution of the errors does not need to be Gaussian (normal) in order for the above definition to apply. It is what is most commonly seen/assumed, however. | |
| Mar 20, 2020 at 21:00 | comment | added | tdMJN6B2JtUe | Incidentally, I would love for anyone in this community to try writing a machine learning algorithm (model) as a linear combination of vector-like quantities. I believe it is impossible to do so, which is why non-linear regression is a thing. | |
| Mar 20, 2020 at 20:59 | history | answered | tdMJN6B2JtUe | CC BY-SA 4.0 |