How to determine which label is considered the 'positive' class in H2O binary classifier?
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Training a binary classifier using h2o.ai and would like to know which label is being considered to be the 'positive' class. This makes a difference since if have labels say, 'give cookie' and 'don't give cookie', and are trying to optimize to maximize recall, depending on which label is the 'positive' class we will be giving out more ('give cookie' is positive class) or less ('don't give cookie' as positive class) cookies.
Another post on SO (How do I specify the positive class in an H2O random forest or other binary classifier?) seems to imply that level values are assigned by alpha order by default ('a' being the lowest level and 'z' being the highest) and just trying to confirm here as it's own explicit question.
Also, is there a way to see which class is currently the 'positive' class for a model (ie. based on the ordering of the confusion matrix labels when using the some_h20_model.confusion_matrix(...) output command)?
h2o
asked Nov 19 at 22:05
lampShadesDrifter
9541626
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Training a binary classifier using h2o.ai and would like to know which label is being considered to be the 'positive' class. This makes a difference since if have labels say, 'give cookie' and 'don't give cookie', and are trying to optimize to maximize recall, depending on which label is the 'positive' class we will be giving out more ('give cookie' is positive class) or less ('don't give cookie' as positive class) cookies.
Another post on SO (How do I specify the positive class in an H2O random forest or other binary classifier?) seems to imply that level values are assigned by alpha order by default ('a' being the lowest level and 'z' being the highest) and just trying to confirm here as it's own explicit question.
Also, is there a way to see which class is currently the 'positive' class for a model (ie. based on the ordering of the confusion matrix labels when using the some_h20_model.confusion_matrix(...) output command)?
h2o
asked Nov 19 at 22:05
lampShadesDrifter
9541626
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Training a binary classifier using h2o.ai and would like to know which label is being considered to be the 'positive' class. This makes a difference since if have labels say, 'give cookie' and 'don't give cookie', and are trying to optimize to maximize recall, depending on which label is the 'positive' class we will be giving out more ('give cookie' is positive class) or less ('don't give cookie' as positive class) cookies.
Another post on SO (How do I specify the positive class in an H2O random forest or other binary classifier?) seems to imply that level values are assigned by alpha order by default ('a' being the lowest level and 'z' being the highest) and just trying to confirm here as it's own explicit question.
Also, is there a way to see which class is currently the 'positive' class for a model (ie. based on the ordering of the confusion matrix labels when using the some_h20_model.confusion_matrix(...) output command)?
h2o
asked Nov 19 at 22:05
lampShadesDrifter
9541626
Training a binary classifier using h2o.ai and would like to know which label is being considered to be the 'positive' class. This makes a difference since if have labels say, 'give cookie' and 'don't give cookie', and are trying to optimize to maximize recall, depending on which label is the 'positive' class we will be giving out more ('give cookie' is positive class) or less ('don't give cookie' as positive class) cookies.
Another post on SO (How do I specify the positive class in an H2O random forest or other binary classifier?) seems to imply that level values are assigned by alpha order by default ('a' being the lowest level and 'z' being the highest) and just trying to confirm here as it's own explicit question.
Also, is there a way to see which class is currently the 'positive' class for a model (ie. based on the ordering of the confusion matrix labels when using the some_h20_model.confusion_matrix(...) output command)?
h2o
h2o
asked Nov 19 at 22:05
lampShadesDrifter
9541626
asked Nov 19 at 22:05
lampShadesDrifter
9541626
asked Nov 19 at 22:05
lampShadesDrifter
9541626
asked Nov 19 at 22:05
lampShadesDrifter
9541626
asked Nov 19 at 22:05
lampShadesDrifter
9541626
9541626
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1 Answer
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What you are verifying is correct, H2O-3 orders levels in lexicographical order.
You can use this confusion matrix as an example of how a confusion matrix will be ordered (i.e. if you have categoricals and you sort them in alphabetical order they will map over to the 0,1,2... as shown)
And here is an example of a binary outcome with No and Yes, where No maps to 0 and Yes maps to 1.
answered Nov 20 at 1:14
Lauren
2,7461515
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
What you are verifying is correct, H2O-3 orders levels in lexicographical order.
You can use this confusion matrix as an example of how a confusion matrix will be ordered (i.e. if you have categoricals and you sort them in alphabetical order they will map over to the 0,1,2... as shown)
And here is an example of a binary outcome with No and Yes, where No maps to 0 and Yes maps to 1.
answered Nov 20 at 1:14
Lauren
2,7461515
add a comment |
up vote
0
down vote
accepted
What you are verifying is correct, H2O-3 orders levels in lexicographical order.
You can use this confusion matrix as an example of how a confusion matrix will be ordered (i.e. if you have categoricals and you sort them in alphabetical order they will map over to the 0,1,2... as shown)
And here is an example of a binary outcome with No and Yes, where No maps to 0 and Yes maps to 1.
answered Nov 20 at 1:14
Lauren
2,7461515
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
What you are verifying is correct, H2O-3 orders levels in lexicographical order.
You can use this confusion matrix as an example of how a confusion matrix will be ordered (i.e. if you have categoricals and you sort them in alphabetical order they will map over to the 0,1,2... as shown)
And here is an example of a binary outcome with No and Yes, where No maps to 0 and Yes maps to 1.
answered Nov 20 at 1:14
Lauren
2,7461515
What you are verifying is correct, H2O-3 orders levels in lexicographical order.
You can use this confusion matrix as an example of how a confusion matrix will be ordered (i.e. if you have categoricals and you sort them in alphabetical order they will map over to the 0,1,2... as shown)
And here is an example of a binary outcome with No and Yes, where No maps to 0 and Yes maps to 1.
answered Nov 20 at 1:14
Lauren
2,7461515
answered Nov 20 at 1:14
Lauren
2,7461515
answered Nov 20 at 1:14
Lauren
2,7461515
answered Nov 20 at 1:14
Lauren
2,7461515
2,7461515
add a comment |
add a comment |
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