What is the name for this classification algorithm?
$begingroup$
Can you help me find the name of this classification method:
Assume we have the following data: $n$ dimensional feature vectors we want to classify in two classes.
- We model the classes as two $n$ dimensional gaussian distributions estimated from the data.
- We classify a new vector to the class that maximizes the PDF (probbility density function) at that point.
classification normal-distribution multivariate-analysis pdf
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
$endgroup$
add a comment |
$begingroup$
Can you help me find the name of this classification method:
Assume we have the following data: $n$ dimensional feature vectors we want to classify in two classes.
- We model the classes as two $n$ dimensional gaussian distributions estimated from the data.
- We classify a new vector to the class that maximizes the PDF (probbility density function) at that point.
classification normal-distribution multivariate-analysis pdf
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
$endgroup$
1
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44
add a comment |
$begingroup$
Can you help me find the name of this classification method:
Assume we have the following data: $n$ dimensional feature vectors we want to classify in two classes.
- We model the classes as two $n$ dimensional gaussian distributions estimated from the data.
- We classify a new vector to the class that maximizes the PDF (probbility density function) at that point.
classification normal-distribution multivariate-analysis pdf
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
$endgroup$
Can you help me find the name of this classification method:
Assume we have the following data: $n$ dimensional feature vectors we want to classify in two classes.
- We model the classes as two $n$ dimensional gaussian distributions estimated from the data.
- We classify a new vector to the class that maximizes the PDF (probbility density function) at that point.
classification normal-distribution multivariate-analysis pdf
classification normal-distribution multivariate-analysis pdf
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
edited Jan 15 at 1:21
Karolis Koncevičius
2,02321426
2,02321426
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
asked Jan 14 at 0:04
SoloNasusSoloNasus
1655
1655
1
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44
add a comment |
1
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44
1
1
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
Probably Quadratic Discriminant Analysis.
There are also names for different constraints you could make:
Covariance matrices of both classes are equal - Linear Discriminant Analysis.
Only diagonal elements of the covariance matrix are non-zero - Naive Bayes Classifier
Covariance matrix is identity (diagonals = 1, non-diagonals = 0) - Nearest Centroid Classifier
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
$endgroup$
add a comment |
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: "65"
};
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
});
}
});
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%2fstats.stackexchange.com%2fquestions%2f387029%2fwhat-is-the-name-for-this-classification-algorithm%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Probably Quadratic Discriminant Analysis.
There are also names for different constraints you could make:
Covariance matrices of both classes are equal - Linear Discriminant Analysis.
Only diagonal elements of the covariance matrix are non-zero - Naive Bayes Classifier
Covariance matrix is identity (diagonals = 1, non-diagonals = 0) - Nearest Centroid Classifier
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
$endgroup$
add a comment |
$begingroup$
Probably Quadratic Discriminant Analysis.
There are also names for different constraints you could make:
Covariance matrices of both classes are equal - Linear Discriminant Analysis.
Only diagonal elements of the covariance matrix are non-zero - Naive Bayes Classifier
Covariance matrix is identity (diagonals = 1, non-diagonals = 0) - Nearest Centroid Classifier
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
$endgroup$
add a comment |
$begingroup$
Probably Quadratic Discriminant Analysis.
There are also names for different constraints you could make:
Covariance matrices of both classes are equal - Linear Discriminant Analysis.
Only diagonal elements of the covariance matrix are non-zero - Naive Bayes Classifier
Covariance matrix is identity (diagonals = 1, non-diagonals = 0) - Nearest Centroid Classifier
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
$endgroup$
Probably Quadratic Discriminant Analysis.
There are also names for different constraints you could make:
Covariance matrices of both classes are equal - Linear Discriminant Analysis.
Only diagonal elements of the covariance matrix are non-zero - Naive Bayes Classifier
Covariance matrix is identity (diagonals = 1, non-diagonals = 0) - Nearest Centroid Classifier
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
edited Jan 14 at 0:43
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
answered Jan 14 at 0:38
Karolis KoncevičiusKarolis Koncevičius
2,02321426
2,02321426
add a comment |
add a comment |
Thanks for contributing an answer to Cross Validated!
- 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%2fstats.stackexchange.com%2fquestions%2f387029%2fwhat-is-the-name-for-this-classification-algorithm%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
1
$begingroup$
Two component Gaussian mixture model?
$endgroup$
– Bey
Jan 14 at 3:44