Additional loss / regularization term based on distance in classification of ordinal classes with neural...
$begingroup$
Sometimes when doing classification with neural networks, there is no ordinal relationship between the target classes. However, if there is, using cross-entropy loss for training, is there a way to add an extra regularization term or loss term that is based on the distance between the predicted class and target class? The goal is of course to give the model the intuition that it is worse to predict class 0 for target 25 than to predict class 24. I was also thinking along the lines of using mean squared error instead of cross-entropy as a loss function but maybe that's unusual for neural networks? Any thoughts or experiences regarding this?
neural-network classification loss-function regularization
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Sometimes when doing classification with neural networks, there is no ordinal relationship between the target classes. However, if there is, using cross-entropy loss for training, is there a way to add an extra regularization term or loss term that is based on the distance between the predicted class and target class? The goal is of course to give the model the intuition that it is worse to predict class 0 for target 25 than to predict class 24. I was also thinking along the lines of using mean squared error instead of cross-entropy as a loss function but maybe that's unusual for neural networks? Any thoughts or experiences regarding this?
neural-network classification loss-function regularization
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago
add a comment |
$begingroup$
Sometimes when doing classification with neural networks, there is no ordinal relationship between the target classes. However, if there is, using cross-entropy loss for training, is there a way to add an extra regularization term or loss term that is based on the distance between the predicted class and target class? The goal is of course to give the model the intuition that it is worse to predict class 0 for target 25 than to predict class 24. I was also thinking along the lines of using mean squared error instead of cross-entropy as a loss function but maybe that's unusual for neural networks? Any thoughts or experiences regarding this?
neural-network classification loss-function regularization
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Sometimes when doing classification with neural networks, there is no ordinal relationship between the target classes. However, if there is, using cross-entropy loss for training, is there a way to add an extra regularization term or loss term that is based on the distance between the predicted class and target class? The goal is of course to give the model the intuition that it is worse to predict class 0 for target 25 than to predict class 24. I was also thinking along the lines of using mean squared error instead of cross-entropy as a loss function but maybe that's unusual for neural networks? Any thoughts or experiences regarding this?
neural-network classification loss-function regularization
neural-network classification loss-function regularization
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 8 hours ago
fast-reflexesfast-reflexes
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 8 hours ago
fast-reflexesfast-reflexes
1011
asked 8 hours ago
fast-reflexesfast-reflexes
1011
1011
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
fast-reflexes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago
add a comment |
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "557"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
fast-reflexes is a new contributor. Be nice, and check out our Code of Conduct.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f48626%2fadditional-loss-regularization-term-based-on-distance-in-classification-of-ord%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
fast-reflexes is a new contributor. Be nice, and check out our Code of Conduct.
fast-reflexes is a new contributor. Be nice, and check out our Code of Conduct.
fast-reflexes is a new contributor. Be nice, and check out our Code of Conduct.
fast-reflexes is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f48626%2fadditional-loss-regularization-term-based-on-distance-in-classification-of-ord%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
$begingroup$
How about treating it as a regression problem, if there is a clear mapping from the classes to scalar values? if your categories are like age ranges "18-24", "25-40", etc, then treat these as a scalar that's the midpoint of the range.
$endgroup$
– Sean Owen♦
7 hours ago