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2

$begingroup$

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are the longitude and latitude for that person.

To test the model, the test set has the fifth row for each person missing in longitude and latitude. What's the best way to approach this problem?

for example the test set looks like:

id time feature2 feature3 long lat
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x 
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x 

etc

machine-learning predictive-modeling algorithms machine-learning-model

share|improve this question

asked Apr 9 at 8:53

principeprincipe

111

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  What’s the time difference between each row from 5-rows?
  $endgroup$
  – pythinker
  Apr 9 at 16:46
  

  
  
  
  

add a comment | 

2

$begingroup$

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are the longitude and latitude for that person.

To test the model, the test set has the fifth row for each person missing in longitude and latitude. What's the best way to approach this problem?

for example the test set looks like:

id time feature2 feature3 long lat
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x 
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x 

etc

machine-learning predictive-modeling algorithms machine-learning-model

share|improve this question

asked Apr 9 at 8:53

principeprincipe

111

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  What’s the time difference between each row from 5-rows?
  $endgroup$
  – pythinker
  Apr 9 at 16:46
  

  
  
  
  

add a comment | 

$begingroup$

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are the longitude and latitude for that person.

To test the model, the test set has the fifth row for each person missing in longitude and latitude. What's the best way to approach this problem?

for example the test set looks like:

id time feature2 feature3 long lat
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x 
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x 

etc

machine-learning predictive-modeling algorithms machine-learning-model

share|improve this question

asked Apr 9 at 8:53

principeprincipe

111

$endgroup$

id time feature2 feature3 long lat
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x number number
1 x x x 
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x number number
2 x x x 

share|improve this question

asked Apr 9 at 8:53

principeprincipe

111

share|improve this question

asked Apr 9 at 8:53

principeprincipe

111

asked Apr 9 at 8:53

principeprincipe

111

asked Apr 9 at 8:53

principeprincipe

111