Machine learning model to predict the best candidate2019 Community Moderator ElectionMachine Learning algorithm to predict an outcome where output is not knownModel building with neural networksUsing neural networks for classification in Hierarchical datawhat is the best approach to my prediction problemSupervised learning for variable length feature-less dataDeep advantage learning: how to predict the valueTraining of Region Proposal Network (RPN)Training a LSTM/any other deep learning model with temporal as well as non temporal attributesStructure the dataset for financial machine learningHow to choose best model checkpoint when training deep learning model on all the data?
A newer friend of my brother's gave him a load of baseball cards that are supposedly extremely valuable. Is this a scam?
How old can references or sources in a thesis be?
What are these boxed doors outside store fronts in New York?
How is the claim "I am in New York only if I am in America" the same as "If I am in New York, then I am in America?
The magic money tree problem
How can I prevent hyper evolved versions of regular creatures from wiping out their cousins?
can i play a electric guitar through a bass amp?
What's the point of deactivating Num Lock on login screens?
Python: next in for loop
Theorems that impeded progress
How did the USSR manage to innovate in an environment characterized by government censorship and high bureaucracy?
How to test if a transaction is standard without spending real money?
How can I make my BBEG immortal short of making them a Lich or Vampire?
Do VLANs within a subnet need to have their own subnet for router on a stick?
Fencing style for blades that can attack from a distance
How does one intimidate enemies without having the capacity for violence?
Can a Warlock become Neutral Good?
How do we improve the relationship with a client software team that performs poorly and is becoming less collaborative?
The use of multiple foreign keys on same column in SQL Server
Is it important to consider tone, melody, and musical form while writing a song?
Mathematical cryptic clues
How to write a macro that is braces sensitive?
Languages that we cannot (dis)prove to be Context-Free
How to say job offer in Mandarin/Cantonese?
Machine learning model to predict the best candidate
2019 Community Moderator ElectionMachine Learning algorithm to predict an outcome where output is not knownModel building with neural networksUsing neural networks for classification in Hierarchical datawhat is the best approach to my prediction problemSupervised learning for variable length feature-less dataDeep advantage learning: how to predict the valueTraining of Region Proposal Network (RPN)Training a LSTM/any other deep learning model with temporal as well as non temporal attributesStructure the dataset for financial machine learningHow to choose best model checkpoint when training deep learning model on all the data?
$begingroup$
I have several training examples, each of which consists of a set of candidates and a label that tells which one of those candidates is the best in that set.
The number of candidates in every set may be different. The set of candidates is unordered. In my current problem, each candidate is represented by a fixed length feature vector. However in future, the number of features describing each candidate may also be different for every candidate.
I would like to build a machine learning model that can predict the best candidate from any given set. What could be a good architecture for such a model?
One approach I tried was a simple MLP that takes one candidate as input and outputs whether or not the candidate is best. But since this MLP wouldn't know which set the candidate belongs to, it fails in situations where a candidate is the best in one set but the same candidate is not the best in another set.
To get a little bit more specific, in my current problem, each candidate is a 2D polyline with a fixed number of line segments. Labelling on the training examples is being done manually to pick the most 'good' looking polyline in a given set of polylines. Each polyline is being described by an array of (x,y) coordinates. Currently each of my polylines contains a fixed number of segments. But in future I may have to support polylines of varying number of segments.
In future, I would also like to extend this to 3D polyhedrons too, but I don't know how to even build a feature vector to describe for 3D polyhedron yet. I guess that's a problem for another day.
machine-learning neural-network prediction machine-learning-model
asked 29 mins ago
MakMak
12
New contributor
Mak 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 |
$begingroup$
I have several training examples, each of which consists of a set of candidates and a label that tells which one of those candidates is the best in that set.
The number of candidates in every set may be different. The set of candidates is unordered. In my current problem, each candidate is represented by a fixed length feature vector. However in future, the number of features describing each candidate may also be different for every candidate.
I would like to build a machine learning model that can predict the best candidate from any given set. What could be a good architecture for such a model?
One approach I tried was a simple MLP that takes one candidate as input and outputs whether or not the candidate is best. But since this MLP wouldn't know which set the candidate belongs to, it fails in situations where a candidate is the best in one set but the same candidate is not the best in another set.
To get a little bit more specific, in my current problem, each candidate is a 2D polyline with a fixed number of line segments. Labelling on the training examples is being done manually to pick the most 'good' looking polyline in a given set of polylines. Each polyline is being described by an array of (x,y) coordinates. Currently each of my polylines contains a fixed number of segments. But in future I may have to support polylines of varying number of segments.
In future, I would also like to extend this to 3D polyhedrons too, but I don't know how to even build a feature vector to describe for 3D polyhedron yet. I guess that's a problem for another day.
machine-learning neural-network prediction machine-learning-model
asked 29 mins ago
MakMak
12
New contributor
Mak 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 |
$begingroup$
I have several training examples, each of which consists of a set of candidates and a label that tells which one of those candidates is the best in that set.
The number of candidates in every set may be different. The set of candidates is unordered. In my current problem, each candidate is represented by a fixed length feature vector. However in future, the number of features describing each candidate may also be different for every candidate.
I would like to build a machine learning model that can predict the best candidate from any given set. What could be a good architecture for such a model?
One approach I tried was a simple MLP that takes one candidate as input and outputs whether or not the candidate is best. But since this MLP wouldn't know which set the candidate belongs to, it fails in situations where a candidate is the best in one set but the same candidate is not the best in another set.
To get a little bit more specific, in my current problem, each candidate is a 2D polyline with a fixed number of line segments. Labelling on the training examples is being done manually to pick the most 'good' looking polyline in a given set of polylines. Each polyline is being described by an array of (x,y) coordinates. Currently each of my polylines contains a fixed number of segments. But in future I may have to support polylines of varying number of segments.
In future, I would also like to extend this to 3D polyhedrons too, but I don't know how to even build a feature vector to describe for 3D polyhedron yet. I guess that's a problem for another day.
machine-learning neural-network prediction machine-learning-model
asked 29 mins ago
MakMak
12
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have several training examples, each of which consists of a set of candidates and a label that tells which one of those candidates is the best in that set.
The number of candidates in every set may be different. The set of candidates is unordered. In my current problem, each candidate is represented by a fixed length feature vector. However in future, the number of features describing each candidate may also be different for every candidate.
I would like to build a machine learning model that can predict the best candidate from any given set. What could be a good architecture for such a model?
One approach I tried was a simple MLP that takes one candidate as input and outputs whether or not the candidate is best. But since this MLP wouldn't know which set the candidate belongs to, it fails in situations where a candidate is the best in one set but the same candidate is not the best in another set.
To get a little bit more specific, in my current problem, each candidate is a 2D polyline with a fixed number of line segments. Labelling on the training examples is being done manually to pick the most 'good' looking polyline in a given set of polylines. Each polyline is being described by an array of (x,y) coordinates. Currently each of my polylines contains a fixed number of segments. But in future I may have to support polylines of varying number of segments.
In future, I would also like to extend this to 3D polyhedrons too, but I don't know how to even build a feature vector to describe for 3D polyhedron yet. I guess that's a problem for another day.
machine-learning neural-network prediction machine-learning-model
machine-learning neural-network prediction machine-learning-model
asked 29 mins ago
MakMak
12
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 29 mins ago
MakMak
12
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 10 mins ago
Mak
asked 29 mins ago
MakMak
12
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 29 mins ago
MakMak
12
asked 29 mins ago
MakMak
12
12
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Mak is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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
);
);
Mak 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%2f48784%2fmachine-learning-model-to-predict-the-best-candidate%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
Mak is a new contributor. Be nice, and check out our Code of Conduct.
Mak is a new contributor. Be nice, and check out our Code of Conduct.
Mak is a new contributor. Be nice, and check out our Code of Conduct.
Mak 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%2f48784%2fmachine-learning-model-to-predict-the-best-candidate%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
