Why do ROSE or SMOTE function changing numeric values?
ROSE and SMOTE function are changing numeric values and I don't know why.
I'm trying to predict hospital readmission in diabetic inpatients and the dataset is highly imbalanced. So I want to use oversampling method to balance my dataset - I've already tried ROSE and SMOTE function.
My dataset contains only numeric values (dummy variables) as I wanted to apply xgboost. But I notice that ROSE and SMOTE are generating non-integer values within variable that is binary.
Should those funtions change original values?
set.seed(1994)
d_split <- initial_split(d.fin, prop = .8)
train <- as.data.table(training(d_split))
test <- as.data.table(testing(d_split))
data.rose <- as.data.table(ROSE(readmitted~., data=train, seed=3)$data)
Original dataset
After applying ROSE function
r modeling oversampling
edited 2 days ago
Mr Shunz
66911726
asked 2 days ago
Michiru
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Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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add a comment |
ROSE and SMOTE function are changing numeric values and I don't know why.
I'm trying to predict hospital readmission in diabetic inpatients and the dataset is highly imbalanced. So I want to use oversampling method to balance my dataset - I've already tried ROSE and SMOTE function.
My dataset contains only numeric values (dummy variables) as I wanted to apply xgboost. But I notice that ROSE and SMOTE are generating non-integer values within variable that is binary.
Should those funtions change original values?
set.seed(1994)
d_split <- initial_split(d.fin, prop = .8)
train <- as.data.table(training(d_split))
test <- as.data.table(testing(d_split))
data.rose <- as.data.table(ROSE(readmitted~., data=train, seed=3)$data)
Original dataset
After applying ROSE function
r modeling oversampling
edited 2 days ago
Mr Shunz
66911726
asked 2 days ago
Michiru
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
1
I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convertinsulinto a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.
– Julius Vainora
2 days ago
add a comment |
ROSE and SMOTE function are changing numeric values and I don't know why.
I'm trying to predict hospital readmission in diabetic inpatients and the dataset is highly imbalanced. So I want to use oversampling method to balance my dataset - I've already tried ROSE and SMOTE function.
My dataset contains only numeric values (dummy variables) as I wanted to apply xgboost. But I notice that ROSE and SMOTE are generating non-integer values within variable that is binary.
Should those funtions change original values?
set.seed(1994)
d_split <- initial_split(d.fin, prop = .8)
train <- as.data.table(training(d_split))
test <- as.data.table(testing(d_split))
data.rose <- as.data.table(ROSE(readmitted~., data=train, seed=3)$data)
Original dataset
After applying ROSE function
r modeling oversampling
edited 2 days ago
Mr Shunz
66911726
asked 2 days ago
Michiru
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
ROSE and SMOTE function are changing numeric values and I don't know why.
I'm trying to predict hospital readmission in diabetic inpatients and the dataset is highly imbalanced. So I want to use oversampling method to balance my dataset - I've already tried ROSE and SMOTE function.
My dataset contains only numeric values (dummy variables) as I wanted to apply xgboost. But I notice that ROSE and SMOTE are generating non-integer values within variable that is binary.
Should those funtions change original values?
set.seed(1994)
d_split <- initial_split(d.fin, prop = .8)
train <- as.data.table(training(d_split))
test <- as.data.table(testing(d_split))
data.rose <- as.data.table(ROSE(readmitted~., data=train, seed=3)$data)
Original dataset
After applying ROSE function
r modeling oversampling
r modeling oversampling
edited 2 days ago
Mr Shunz
66911726
asked 2 days ago
Michiru
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 days ago
Mr Shunz
66911726
asked 2 days ago
Michiru
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 days ago
Mr Shunz
66911726
edited 2 days ago
Mr Shunz
66911726
edited 2 days ago
Mr Shunz
66911726
66911726
asked 2 days ago
Michiru
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
Michiru
12
asked 2 days ago
Michiru
12
12
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Michiru is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
1
I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convertinsulinto a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.
– Julius Vainora
2 days ago
add a comment |
1
I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convertinsulinto a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.
– Julius Vainora
2 days ago
1
1
I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convert
insulin to a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.– Julius Vainora
2 days ago
I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convert
insulin to a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.– Julius Vainora
2 days ago
add a comment |
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I'm not sure about the range of new values, but if a variable is considered numeric, then SMOTE creates new values with convex combinations of the existent ones. Hence, all values between 0 and 1 become possible. What you want then, I guess, is to convert
insulinto a factor variable. In that case, stackoverflow.com/a/53653693/1320535 is relevant.– Julius Vainora
2 days ago