Hierarchical Clustering and Variable Selection
$begingroup$
I am using "Single linkage" hierarchical algorithm to cluster my data points with Gower Distance as my data have both qualitative and quantitative variables.
After applying this for the full model (all variables) I would like to start excluding those variables which are actually the not so important for my data. I was thinking of using principal component analysis (PCA) but I can't because my variables are a mixture of both categorical and continuous. Can someone suggest what is best method to select variables?
Finally I would like to use the Elbow Method to check exactly what is the optimal number of clusters?
Can someone help me with this logic?
I am using R-Studio for my analysis.
r clustering feature-selection
New contributor
$endgroup$
add a comment |
$begingroup$
I am using "Single linkage" hierarchical algorithm to cluster my data points with Gower Distance as my data have both qualitative and quantitative variables.
After applying this for the full model (all variables) I would like to start excluding those variables which are actually the not so important for my data. I was thinking of using principal component analysis (PCA) but I can't because my variables are a mixture of both categorical and continuous. Can someone suggest what is best method to select variables?
Finally I would like to use the Elbow Method to check exactly what is the optimal number of clusters?
Can someone help me with this logic?
I am using R-Studio for my analysis.
r clustering feature-selection
New contributor
$endgroup$
add a comment |
$begingroup$
I am using "Single linkage" hierarchical algorithm to cluster my data points with Gower Distance as my data have both qualitative and quantitative variables.
After applying this for the full model (all variables) I would like to start excluding those variables which are actually the not so important for my data. I was thinking of using principal component analysis (PCA) but I can't because my variables are a mixture of both categorical and continuous. Can someone suggest what is best method to select variables?
Finally I would like to use the Elbow Method to check exactly what is the optimal number of clusters?
Can someone help me with this logic?
I am using R-Studio for my analysis.
r clustering feature-selection
New contributor
$endgroup$
I am using "Single linkage" hierarchical algorithm to cluster my data points with Gower Distance as my data have both qualitative and quantitative variables.
After applying this for the full model (all variables) I would like to start excluding those variables which are actually the not so important for my data. I was thinking of using principal component analysis (PCA) but I can't because my variables are a mixture of both categorical and continuous. Can someone suggest what is best method to select variables?
Finally I would like to use the Elbow Method to check exactly what is the optimal number of clusters?
Can someone help me with this logic?
I am using R-Studio for my analysis.
r clustering feature-selection
r clustering feature-selection
New contributor
New contributor
New contributor
asked 2 days ago
Annalise AzzopardiAnnalise Azzopardi
1
1
New contributor
New contributor
add a comment |
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
});
}
});
Annalise Azzopardi 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%2f46632%2fhierarchical-clustering-and-variable-selection%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
Annalise Azzopardi is a new contributor. Be nice, and check out our Code of Conduct.
Annalise Azzopardi is a new contributor. Be nice, and check out our Code of Conduct.
Annalise Azzopardi is a new contributor. Be nice, and check out our Code of Conduct.
Annalise Azzopardi 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%2f46632%2fhierarchical-clustering-and-variable-selection%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