How to handle columns with categorical data and many unique values2019 Community Moderator Electiondecision...
Patience, young "Padovan"
Hosting Wordpress in a EC2 Load Balanced Instance
Are objects structures and/or vice versa?
Why did the Germans forbid the possession of pet pigeons in Rostov-on-Don in 1941?
Why airport relocation isn't done gradually?
Is "plugging out" electronic devices an American expression?
What do the Banks children have against barley water?
Are white and non-white police officers equally likely to kill black suspects?
Doomsday-clock for my fantasy planet
Is there any use for defining additional entity types in a SOQL FROM clause?
How could a lack of term limits lead to a "dictatorship?"
Typesetting a double Over Dot on top of a symbol
Unbreakable Formation vs. Cry of the Carnarium
Information to fellow intern about hiring?
Ideas for 3rd eye abilities
When blogging recipes, how can I support both readers who want the narrative/journey and ones who want the printer-friendly recipe?
Copycat chess is back
Prime joint compound before latex paint?
Denied boarding due to overcrowding, Sparpreis ticket. What are my rights?
New order #4: World
Can the Produce Flame cantrip be used to grapple, or as an unarmed strike, in the right circumstances?
Why do UK politicians seemingly ignore opinion polls on Brexit?
extract characters between two commas?
Is there a name of the flying bionic bird?
How to handle columns with categorical data and many unique values
2019 Community Moderator Electiondecision trees on mix of categorical and real value parametersPandas categorical variables encoding for regression (one-hot encoding vs dummy encoding)Imputation of missing values and dealing with categorical valuesHow to deal with categorical variablesOne hot encoding error “sort.list(y)…”One hot encoding vs Word embeddingHow to implement feature selection for categorical variables (especially with many categories)?ML Models: How to handle categorical feature with over 1000 unique values“Binary Encoding” in “Decision Tree” / “Random Forest” AlgorithmsDealing with multiple distinct-value categorical variables
$begingroup$
I have a column with categorical data with nunique 3349 values, in a 18000k row dataset, which represent cities of the world.
I also have another column with 145 nunique values that I could also use in my model that represents product category.
Can I use one hot encoding to these columns or there's a problem with that solution?
Like which is the max number of unique values to use one hot encoding so there's not gonna be any problem ?
Can you point me to the right direction if I should use another encoding also?
machine-learning data categorical-data encoding
asked 19 hours ago
dungeondungeon
293
$endgroup$
add a comment |
$begingroup$
I have a column with categorical data with nunique 3349 values, in a 18000k row dataset, which represent cities of the world.
I also have another column with 145 nunique values that I could also use in my model that represents product category.
Can I use one hot encoding to these columns or there's a problem with that solution?
Like which is the max number of unique values to use one hot encoding so there's not gonna be any problem ?
Can you point me to the right direction if I should use another encoding also?
machine-learning data categorical-data encoding
asked 19 hours ago
dungeondungeon
293
$endgroup$
add a comment |
$begingroup$
I have a column with categorical data with nunique 3349 values, in a 18000k row dataset, which represent cities of the world.
I also have another column with 145 nunique values that I could also use in my model that represents product category.
Can I use one hot encoding to these columns or there's a problem with that solution?
Like which is the max number of unique values to use one hot encoding so there's not gonna be any problem ?
Can you point me to the right direction if I should use another encoding also?
machine-learning data categorical-data encoding
asked 19 hours ago
dungeondungeon
293
$endgroup$
I have a column with categorical data with nunique 3349 values, in a 18000k row dataset, which represent cities of the world.
I also have another column with 145 nunique values that I could also use in my model that represents product category.
Can I use one hot encoding to these columns or there's a problem with that solution?
Like which is the max number of unique values to use one hot encoding so there's not gonna be any problem ?
Can you point me to the right direction if I should use another encoding also?
machine-learning data categorical-data encoding
machine-learning data categorical-data encoding
asked 19 hours ago
dungeondungeon
293
asked 19 hours ago
dungeondungeon
293
asked 19 hours ago
dungeondungeon
293
asked 19 hours ago
dungeondungeon
293
asked 19 hours ago
dungeondungeon
293
293
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
For categorical columns, you have two options :
- Entity Embeddings
- One Hot Vector
For a column with 145 values, I would use one hot encoding and Embedding for ~3k values. This decision might change depending on overall number of features.
Embeddings map feature values into a 1D vector so that model knows NYC, Paris, London are similar cities in one aspect (size) and very different in other aspects. So, instead of using ~3k column of features, model will have ~50 columns of vector representation.
Articles that explain Embeddings :
An Overview of Categorical Input Handling for Neural Networks
On learning embeddings for categorical data using Keras
Google Developers > Machine Learning > Embeddings: Categorical Input Data
Exploring Embeddings for Categorical Variables with Keras by Florian Teschner
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
$endgroup$
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: "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%2f48875%2fhow-to-handle-columns-with-categorical-data-and-many-unique-values%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
$begingroup$
For categorical columns, you have two options :
- Entity Embeddings
- One Hot Vector
For a column with 145 values, I would use one hot encoding and Embedding for ~3k values. This decision might change depending on overall number of features.
Embeddings map feature values into a 1D vector so that model knows NYC, Paris, London are similar cities in one aspect (size) and very different in other aspects. So, instead of using ~3k column of features, model will have ~50 columns of vector representation.
Articles that explain Embeddings :
An Overview of Categorical Input Handling for Neural Networks
On learning embeddings for categorical data using Keras
Google Developers > Machine Learning > Embeddings: Categorical Input Data
Exploring Embeddings for Categorical Variables with Keras by Florian Teschner
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
$endgroup$
add a comment |
$begingroup$
For categorical columns, you have two options :
- Entity Embeddings
- One Hot Vector
For a column with 145 values, I would use one hot encoding and Embedding for ~3k values. This decision might change depending on overall number of features.
Embeddings map feature values into a 1D vector so that model knows NYC, Paris, London are similar cities in one aspect (size) and very different in other aspects. So, instead of using ~3k column of features, model will have ~50 columns of vector representation.
Articles that explain Embeddings :
An Overview of Categorical Input Handling for Neural Networks
On learning embeddings for categorical data using Keras
Google Developers > Machine Learning > Embeddings: Categorical Input Data
Exploring Embeddings for Categorical Variables with Keras by Florian Teschner
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
$endgroup$
add a comment |
$begingroup$
For categorical columns, you have two options :
- Entity Embeddings
- One Hot Vector
For a column with 145 values, I would use one hot encoding and Embedding for ~3k values. This decision might change depending on overall number of features.
Embeddings map feature values into a 1D vector so that model knows NYC, Paris, London are similar cities in one aspect (size) and very different in other aspects. So, instead of using ~3k column of features, model will have ~50 columns of vector representation.
Articles that explain Embeddings :
An Overview of Categorical Input Handling for Neural Networks
On learning embeddings for categorical data using Keras
Google Developers > Machine Learning > Embeddings: Categorical Input Data
Exploring Embeddings for Categorical Variables with Keras by Florian Teschner
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
$endgroup$
For categorical columns, you have two options :
- Entity Embeddings
- One Hot Vector
For a column with 145 values, I would use one hot encoding and Embedding for ~3k values. This decision might change depending on overall number of features.
Embeddings map feature values into a 1D vector so that model knows NYC, Paris, London are similar cities in one aspect (size) and very different in other aspects. So, instead of using ~3k column of features, model will have ~50 columns of vector representation.
Articles that explain Embeddings :
An Overview of Categorical Input Handling for Neural Networks
On learning embeddings for categorical data using Keras
Google Developers > Machine Learning > Embeddings: Categorical Input Data
Exploring Embeddings for Categorical Variables with Keras by Florian Teschner
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
edited 15 hours ago
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
answered 18 hours ago
Shamit VermaShamit Verma
1,4841214
1,4841214
add a comment |
add a comment |
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%2f48875%2fhow-to-handle-columns-with-categorical-data-and-many-unique-values%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
