Mixing
Finding relationship between variables
There are two sets:
A: 1 2 3
B : 1 2 3 4 5 6 7 8 9 10
Points in A serve to multiple points in B. for example:
A 1: B 1 2 4
A 2: B 3 5 6
A 3: B 7 8 9 10
Given historical data of points in both A and B set, how to determine the which point in A is serving to points in set B?
data-science correlation supervised-learning unsupervised-learning
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
add a comment |
There are two sets:
A: 1 2 3
B : 1 2 3 4 5 6 7 8 9 10
Points in A serve to multiple points in B. for example:
A 1: B 1 2 4
A 2: B 3 5 6
A 3: B 7 8 9 10
Given historical data of points in both A and B set, how to determine the which point in A is serving to points in set B?
data-science correlation supervised-learning unsupervised-learning
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
add a comment |
There are two sets:
A: 1 2 3
B : 1 2 3 4 5 6 7 8 9 10
Points in A serve to multiple points in B. for example:
A 1: B 1 2 4
A 2: B 3 5 6
A 3: B 7 8 9 10
Given historical data of points in both A and B set, how to determine the which point in A is serving to points in set B?
data-science correlation supervised-learning unsupervised-learning
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
There are two sets:
A: 1 2 3
B : 1 2 3 4 5 6 7 8 9 10
Points in A serve to multiple points in B. for example:
A 1: B 1 2 4
A 2: B 3 5 6
A 3: B 7 8 9 10
Given historical data of points in both A and B set, how to determine the which point in A is serving to points in set B?
data-science correlation supervised-learning unsupervised-learning
data-science correlation supervised-learning unsupervised-learning
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
asked Jan 1 at 21:10
Prajakta GujarathiPrajakta Gujarathi
31
31
add a comment |
add a comment |
1 Answer
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Encode A and B columns as vectors and fit classification model. Then, after fitting, you can make predictions for various inputs of A ((1, 0, 0) as an example) and get probabilities in vector B ((0.25, 0.5, 0.1, ..., 0.15) as an example). So, in this case, value 1 for A serves values (1, 2, 3, 10) with probabilities above. Depending on the task, you can select some threshold.
Depending on the data you need to select an encoding method (dummy vs one-hot), model, think about sampling, metric and so on.
answered Jan 2 at 8:38
avchauzovavchauzov
734310
add a comment |
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1 Answer
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1 Answer
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active
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Encode A and B columns as vectors and fit classification model. Then, after fitting, you can make predictions for various inputs of A ((1, 0, 0) as an example) and get probabilities in vector B ((0.25, 0.5, 0.1, ..., 0.15) as an example). So, in this case, value 1 for A serves values (1, 2, 3, 10) with probabilities above. Depending on the task, you can select some threshold.
Depending on the data you need to select an encoding method (dummy vs one-hot), model, think about sampling, metric and so on.
answered Jan 2 at 8:38
avchauzovavchauzov
734310
add a comment |
Encode A and B columns as vectors and fit classification model. Then, after fitting, you can make predictions for various inputs of A ((1, 0, 0) as an example) and get probabilities in vector B ((0.25, 0.5, 0.1, ..., 0.15) as an example). So, in this case, value 1 for A serves values (1, 2, 3, 10) with probabilities above. Depending on the task, you can select some threshold.
Depending on the data you need to select an encoding method (dummy vs one-hot), model, think about sampling, metric and so on.
answered Jan 2 at 8:38
avchauzovavchauzov
734310
add a comment |
Encode A and B columns as vectors and fit classification model. Then, after fitting, you can make predictions for various inputs of A ((1, 0, 0) as an example) and get probabilities in vector B ((0.25, 0.5, 0.1, ..., 0.15) as an example). So, in this case, value 1 for A serves values (1, 2, 3, 10) with probabilities above. Depending on the task, you can select some threshold.
Depending on the data you need to select an encoding method (dummy vs one-hot), model, think about sampling, metric and so on.
answered Jan 2 at 8:38
avchauzovavchauzov
734310
Encode A and B columns as vectors and fit classification model. Then, after fitting, you can make predictions for various inputs of A ((1, 0, 0) as an example) and get probabilities in vector B ((0.25, 0.5, 0.1, ..., 0.15) as an example). So, in this case, value 1 for A serves values (1, 2, 3, 10) with probabilities above. Depending on the task, you can select some threshold.
Depending on the data you need to select an encoding method (dummy vs one-hot), model, think about sampling, metric and so on.
answered Jan 2 at 8:38
avchauzovavchauzov
734310
answered Jan 2 at 8:38
avchauzovavchauzov
734310
answered Jan 2 at 8:38
avchauzovavchauzov
734310
answered Jan 2 at 8:38
avchauzovavchauzov
734310
734310
add a comment |
add a comment |
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