How to determine the weights of features when calculating the weighted average?
$begingroup$
I have a dataset of Tweets along with their Retweet Counts and Favorite Counts. After extracting features from the Tweets, I am training a model to predict the Retweet Counts and Favorite Counts. I want to calculate a value called "Popularity" by taking the weighted average of Retweet Count and Favorite Count for each Tweet. For this, I need score values (or weights) for Retweet Count and Favorite Count. How do I determine these weights?
I am writing a research paper and need to justify why I assigned those weights for Retweet Count and Favorite Count.
machine-learning data
$endgroup$
add a comment |
$begingroup$
I have a dataset of Tweets along with their Retweet Counts and Favorite Counts. After extracting features from the Tweets, I am training a model to predict the Retweet Counts and Favorite Counts. I want to calculate a value called "Popularity" by taking the weighted average of Retweet Count and Favorite Count for each Tweet. For this, I need score values (or weights) for Retweet Count and Favorite Count. How do I determine these weights?
I am writing a research paper and need to justify why I assigned those weights for Retweet Count and Favorite Count.
machine-learning data
$endgroup$
add a comment |
$begingroup$
I have a dataset of Tweets along with their Retweet Counts and Favorite Counts. After extracting features from the Tweets, I am training a model to predict the Retweet Counts and Favorite Counts. I want to calculate a value called "Popularity" by taking the weighted average of Retweet Count and Favorite Count for each Tweet. For this, I need score values (or weights) for Retweet Count and Favorite Count. How do I determine these weights?
I am writing a research paper and need to justify why I assigned those weights for Retweet Count and Favorite Count.
machine-learning data
$endgroup$
I have a dataset of Tweets along with their Retweet Counts and Favorite Counts. After extracting features from the Tweets, I am training a model to predict the Retweet Counts and Favorite Counts. I want to calculate a value called "Popularity" by taking the weighted average of Retweet Count and Favorite Count for each Tweet. For this, I need score values (or weights) for Retweet Count and Favorite Count. How do I determine these weights?
I am writing a research paper and need to justify why I assigned those weights for Retweet Count and Favorite Count.
machine-learning data
machine-learning data
asked 19 mins ago
KabileshKabilesh
61
61
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
});
}
});
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%2f45331%2fhow-to-determine-the-weights-of-features-when-calculating-the-weighted-average%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
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%2f45331%2fhow-to-determine-the-weights-of-features-when-calculating-the-weighted-average%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