Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with loss-functions
Search options not deleted
user 263447
A function used to quantify the difference between observed data and predicted values according to a model. Minimization of loss functions is a way to estimate the parameters of the model.
0
votes
0
answers
23
views
Why doesn't a divisive loss function $\frac{\hat{y}}{y} + \frac{y}{\hat{y}}$ work better tha... [merged]
Suppose you had a classification problem where you are trying to predict a class label (e.g., $[0 \: 1 \: 0]^T$) with a model. One way to do this is to use log loss:
$\Large L_{\log} = -\sum_i[y_i\lo …
- 277
0
votes
0
answers
141
views
If you're trying to match a vector $p$ to $x$, why doesn't a divisive loss function $\frac{p... [duplicate]
Suppose you had a classification problem where you are trying to predict a class label (e.g., $[0 \: 1 \: 0]^T$) with a model. One way to do this is to use log loss:
$\Large \ell_{\log} = -\sum_i[y_i …
- 277
7
votes
1
answer
2k
views
How does one design a custom loss function? What features make a loss function "good"?
I have a custom situation for which I am trying to design a cost function.
The idea is that you have a stack of LSTMs doing something slightly unconventional. Each LSTM$_l$ computes a linear transform …
- 277