Timeline for Decomposing MSE: Variance bias, or variance, bias AND noise?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 9, 2016 at 13:10 | comment | added | Christoph Hanck | Maybe it was tacitly ignored as we cannot do anything about the irreducible part anyhow. | |
| Dec 9, 2016 at 13:08 | comment | added | Tony | unfortunately it's from a private course materials. But there really isn't anything more to it. g(t) is the fit and ^g(t) is its estimate. | |
| Dec 9, 2016 at 13:03 | comment | added | Christoph Hanck | That is tough to say without knowing what $g$ precisely is. Can you provide a reference? | |
| Dec 9, 2016 at 13:02 | comment | added | Tony | I was also able to find a source that says: $MSE[ˆ g(t)] = [E(ˆ g(t)−g(t))]^2 + V ar(ˆ g(t))$. Derived from $MSE[ˆ g(t)] = E[(ˆ g(t)−g(t))^2]$. Nowhere is it stated that the noise is 0. Is this a mistake? | |
| Dec 9, 2016 at 12:45 | vote | accept | Tony | ||
| Dec 9, 2016 at 12:34 | history | answered | Christoph Hanck | CC BY-SA 3.0 |