Trjtdtk

Could the E-bike drivetrain wear down till needing replacement after 400 km?

Can somebody explain the brexit thing in one or two child-proof sentences?

Customize circled numbers

Varistor? Purpose and principle

Can I use Seifert-van Kampen theorem infinite times

Why should universal income be universal?

Pre-mixing cryogenic fuels and using only one fuel tank

How can Trident be so inexpensive? Will it orbit Triton or just do a (slow) flyby?

What spells are affected by the size of the caster?

What linear sensor for a keybaord?

Is there a single word describing earning money through any means?

Store Credit Card Information in Password Manager?

why `nmap 192.168.1.97` returns less services than `nmap 127.0.0.1`?

hline - width of entire table

Did arcade monitors have same pixel aspect ratio as TV sets?

Can I sign legal documents with a smiley face?

Does an advisor owe his/her student anything? Will an advisor keep a PhD student only out of pity?

Argument list too long when zipping large list of certain files in a folder

How to explain what's wrong with this application of the chain rule?

Is there an efficient solution to the travelling salesman problem with binary edge weights?

Biological Blimps: Propulsion

Is it possible to have a strip of cold climate in the middle of a planet?

Loading commands from file

Should I stop contributing to retirement accounts?

How exactly do I extract the important features from strings for machine learning?

How to choose the features for a neural network?Machine learning - features engineering from date/time dataHow to select features from text data?Identifying important interactions between features using machine learningFilling missing values for important featuresThe automatic construction of new features from raw dataHow to extract relative importance of features from a tensorflow DNNRegressor model?Using python and machine learning to extract information from an invoice? Inital dataset?Extract features from a surveyHow exactly do I go about extracting features from timestamps for machine learning?

0

$begingroup$

Forgive me for my ignorance. Linked below is an image of my dataset with 1000 tuples.

https://i.stack.imgur.com/WHIlx.png

I have the following questions
(1) How exactly do I go about extracting information from the Ad topic line?
(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't the large number of countries/cities be a problem?)

Thank you so much for your time. All help is greatly appreciated.

machine-learning feature-selection feature-extraction feature-engineering

share|improve this question

edited Mar 20 at 6:17

Apollo

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo 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 | 

0

$begingroup$

Forgive me for my ignorance. Linked below is an image of my dataset with 1000 tuples.

https://i.stack.imgur.com/WHIlx.png

I have the following questions
(1) How exactly do I go about extracting information from the Ad topic line?
(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't the large number of countries/cities be a problem?)

Thank you so much for your time. All help is greatly appreciated.

machine-learning feature-selection feature-extraction feature-engineering

share|improve this question

edited Mar 20 at 6:17

Apollo

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo 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 | 

$begingroup$

Forgive me for my ignorance. Linked below is an image of my dataset with 1000 tuples.

https://i.stack.imgur.com/WHIlx.png

I have the following questions
(1) How exactly do I go about extracting information from the Ad topic line?
(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't the large number of countries/cities be a problem?)

Thank you so much for your time. All help is greatly appreciated.

machine-learning feature-selection feature-extraction feature-engineering

share|improve this question

edited Mar 20 at 6:17

Apollo

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

edited Mar 20 at 6:17

Apollo

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited Mar 20 at 6:17

Apollo

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked Mar 19 at 20:29

ApolloApollo

61

New contributor

Apollo is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked Mar 19 at 20:29

ApolloApollo

61

1 Answer
1

active

oldest

votes

0

$begingroup$

(1) How exactly do I go about extracting information from the Ad topic line?

The best way to deal with the test string is to Convert it into a term-document matrix and calculate the TFIDF Scores for every word in the string.

(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't a large number of countries/cities be a problem?)

Yes you said the right large number of cities will be a problem i suggest still you can go with that, Rather there is a way find out the distribution of all your cities and cities and convert them into integers.
Even another way could be give weights to the cities which are repeated most,let me give you an example:

Suppose you have 10 observations and 5 cities A(5 times),B(2 times),C(once),D(Once),E(Once):

so A will get a weight of 5/10=0.5 which B will get a weight of 2/10=0.2 and so on.

Hope this helps!

share|improve this answer

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thank you for your response! Could you please walk me through the matrix conversion and score calculation in python?
  $endgroup$
  – Apollo
  22 hours ago
  

  
  
  
  

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
);



);

Apollo is a new contributor. Be nice, and check out our Code of Conduct.

draft saved

draft discarded

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

Name

Email

Required, but never shown

StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47640%2fhow-exactly-do-i-extract-the-important-features-from-strings-for-machine-learnin%23new-answer', 'question_page');

);

Post as a guest

Name

Email

Required, but never shown

0

$begingroup$

(1) How exactly do I go about extracting information from the Ad topic line?

The best way to deal with the test string is to Convert it into a term-document matrix and calculate the TFIDF Scores for every word in the string.

(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't a large number of countries/cities be a problem?)

Yes you said the right large number of cities will be a problem i suggest still you can go with that, Rather there is a way find out the distribution of all your cities and cities and convert them into integers.
Even another way could be give weights to the cities which are repeated most,let me give you an example:

Suppose you have 10 observations and 5 cities A(5 times),B(2 times),C(once),D(Once),E(Once):

so A will get a weight of 5/10=0.5 which B will get a weight of 2/10=0.2 and so on.

Hope this helps!

share|improve this answer

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thank you for your response! Could you please walk me through the matrix conversion and score calculation in python?
  $endgroup$
  – Apollo
  22 hours ago
  

  
  
  
  

add a comment | 

0

$begingroup$

(1) How exactly do I go about extracting information from the Ad topic line?

The best way to deal with the test string is to Convert it into a term-document matrix and calculate the TFIDF Scores for every word in the string.

(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't a large number of countries/cities be a problem?)

Yes you said the right large number of cities will be a problem i suggest still you can go with that, Rather there is a way find out the distribution of all your cities and cities and convert them into integers.
Even another way could be give weights to the cities which are repeated most,let me give you an example:

Suppose you have 10 observations and 5 cities A(5 times),B(2 times),C(once),D(Once),E(Once):

so A will get a weight of 5/10=0.5 which B will get a weight of 2/10=0.2 and so on.

Hope this helps!

share|improve this answer

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Thank you for your response! Could you please walk me through the matrix conversion and score calculation in python?
  $endgroup$
  – Apollo
  22 hours ago
  

  
  
  
  

add a comment | 

$begingroup$

(1) How exactly do I go about extracting information from the Ad topic line?

The best way to deal with the test string is to Convert it into a term-document matrix and calculate the TFIDF Scores for every word in the string.

(2) How should I approach the categorical variables Country and City? ( I've heard about encoding but won't a large number of countries/cities be a problem?)

Yes you said the right large number of cities will be a problem i suggest still you can go with that, Rather there is a way find out the distribution of all your cities and cities and convert them into integers.
Even another way could be give weights to the cities which are repeated most,let me give you an example:

Suppose you have 10 observations and 5 cities A(5 times),B(2 times),C(once),D(Once),E(Once):

so A will get a weight of 5/10=0.5 which B will get a weight of 2/10=0.2 and so on.

Hope this helps!

share|improve this answer

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

$endgroup$

share|improve this answer

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112

answered Mar 20 at 11:05

Kartik PatnaikKartik Patnaik

112