Timeline for Convert the following expression w.r.t to the whole dataset instead of element of the dataset?
Current License: CC BY-SA 4.0
12 events
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| Sep 20, 2020 at 18:15 | comment | added | Javier TG | Ah sorry, in your first comment I read $X^T\alpha$ instead of $\alpha^TX$. If you do $\alpha^TX$ then we obtain $w^T$, as you have just correctly said ($w^T=(X^T\alpha)^T$). But of course, it would be the same $w$, just transposed. | |
| Sep 20, 2020 at 18:11 | comment | added | cIckalakba | With the above example, if I use $w=\alpha^T X$ I would get an answer with a different dimension. Mathematically $(\alpha^T X) = (X^T \alpha)^T$ resulting essentially different $w$, how could both of them be valid conversions from $\sum^N_{i=1}\alpha_i x_i$, What did I miss? | |
| Sep 20, 2020 at 18:03 | comment | added | Javier TG | I edited the answer with a simple example so you can ckeck it | |
| Sep 20, 2020 at 18:02 | history | edited | Javier TG | CC BY-SA 4.0 |
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| Sep 20, 2020 at 17:55 | vote | accept | cIckalakba | ||
| Sep 20, 2020 at 17:55 | comment | added | cIckalakba | This is interesting, thank you for the answers! | |
| Sep 20, 2020 at 17:53 | comment | added | Javier TG | Yes, it is equivalent. If you want, you can try to do a simple example by hand and check it. | |
| Sep 20, 2020 at 17:51 | comment | added | cIckalakba | Is it valid that $$w=\alpha^T X$$ can also be formulated as $$w = \sum ^N _{i=1} \alpha_i x_i$$? In this case the resulting dimension of w would be different? I am a bit confused about this.. | |
| Sep 20, 2020 at 17:30 | history | edited | Javier TG | CC BY-SA 4.0 |
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| Sep 20, 2020 at 15:43 | history | edited | Javier TG | CC BY-SA 4.0 |
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| Sep 20, 2020 at 15:37 | history | edited | Javier TG | CC BY-SA 4.0 |
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| Sep 20, 2020 at 15:30 | history | answered | Javier TG | CC BY-SA 4.0 |