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Making Prediction on logistic regression using SAS

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0

$begingroup$

proc logistic data= train descending;
 class Emp_status Gender Marital_status;
 model Default = Checking_amount Term Credit_score Gender Marital_status 
 Car_loan Personal_loan Home_loan Education_loan Emp_status 
 Amount Saving_amount Emp_duration Age No_of_credit_acc;
run;

As you can see, I already made a logistic regression on train dataset. However, how can I make the prediction on the test dataset? I checked online, but there are not many sources to implement this.

logistic-regression prediction sas

share|improve this question

asked Apr 9 at 1:41

TomTom

91111

$endgroup$

add a comment | 

0

$begingroup$

proc logistic data= train descending;
 class Emp_status Gender Marital_status;
 model Default = Checking_amount Term Credit_score Gender Marital_status 
 Car_loan Personal_loan Home_loan Education_loan Emp_status 
 Amount Saving_amount Emp_duration Age No_of_credit_acc;
run;

As you can see, I already made a logistic regression on train dataset. However, how can I make the prediction on the test dataset? I checked online, but there are not many sources to implement this.

logistic-regression prediction sas

share|improve this question

asked Apr 9 at 1:41

TomTom

91111

$endgroup$

add a comment | 

$begingroup$

proc logistic data= train descending;
 class Emp_status Gender Marital_status;
 model Default = Checking_amount Term Credit_score Gender Marital_status 
 Car_loan Personal_loan Home_loan Education_loan Emp_status 
 Amount Saving_amount Emp_duration Age No_of_credit_acc;
run;

As you can see, I already made a logistic regression on train dataset. However, how can I make the prediction on the test dataset? I checked online, but there are not many sources to implement this.

logistic-regression prediction sas

share|improve this question

asked Apr 9 at 1:41

TomTom

91111

$endgroup$

proc logistic data= train descending;
 class Emp_status Gender Marital_status;
 model Default = Checking_amount Term Credit_score Gender Marital_status 
 Car_loan Personal_loan Home_loan Education_loan Emp_status 
 Amount Saving_amount Emp_duration Age No_of_credit_acc;
run;

share|improve this question

asked Apr 9 at 1:41

TomTom

91111

share|improve this question

asked Apr 9 at 1:41

TomTom

91111

asked Apr 9 at 1:41

TomTom

91111

asked Apr 9 at 1:41

TomTom

91111

1 Answer
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oldest

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1

$begingroup$

proc surveyselect data=work.data method=srs seed=2 outall
samprate=0.7 out=work.data_subset;

data training;
set work.data_subset; *dataset in your work directory;
if selected = 1;
run;

data testing;
set work.data_subset; *dataset in your working directory;
if selected = 0;
run;

ods graphics on;
proc logistic data=work.training descending plots=roc;
class Gender /param = effect ref = first; *categorical variable;
model default = x1 x2 x3 x4 x5
/ link=logit;
score data=work.testing out=work.logisticOoutput;
run;
ods graphics off;

Using proc surveyselect to split the dataset 70% 30%, we can split our dataset into train and test. Then, we can run logistic regression on train data. see the performance on the test dataset.

score data=work.testing 

This command is running the regression on the test set. see the result in the output.

share|improve this answer

answered Apr 20 at 0:28

TomTom

91111

$endgroup$

add a comment | 

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1

$begingroup$

proc surveyselect data=work.data method=srs seed=2 outall
samprate=0.7 out=work.data_subset;

data training;
set work.data_subset; *dataset in your work directory;
if selected = 1;
run;

data testing;
set work.data_subset; *dataset in your working directory;
if selected = 0;
run;

ods graphics on;
proc logistic data=work.training descending plots=roc;
class Gender /param = effect ref = first; *categorical variable;
model default = x1 x2 x3 x4 x5
/ link=logit;
score data=work.testing out=work.logisticOoutput;
run;
ods graphics off;

Using proc surveyselect to split the dataset 70% 30%, we can split our dataset into train and test. Then, we can run logistic regression on train data. see the performance on the test dataset.

score data=work.testing 

This command is running the regression on the test set. see the result in the output.

share|improve this answer

answered Apr 20 at 0:28

TomTom

91111

$endgroup$

add a comment | 

1

$begingroup$

proc surveyselect data=work.data method=srs seed=2 outall
samprate=0.7 out=work.data_subset;

data training;
set work.data_subset; *dataset in your work directory;
if selected = 1;
run;

data testing;
set work.data_subset; *dataset in your working directory;
if selected = 0;
run;

ods graphics on;
proc logistic data=work.training descending plots=roc;
class Gender /param = effect ref = first; *categorical variable;
model default = x1 x2 x3 x4 x5
/ link=logit;
score data=work.testing out=work.logisticOoutput;
run;
ods graphics off;

Using proc surveyselect to split the dataset 70% 30%, we can split our dataset into train and test. Then, we can run logistic regression on train data. see the performance on the test dataset.

score data=work.testing 

This command is running the regression on the test set. see the result in the output.

share|improve this answer

answered Apr 20 at 0:28

TomTom

91111

$endgroup$

add a comment | 

$begingroup$

proc surveyselect data=work.data method=srs seed=2 outall
samprate=0.7 out=work.data_subset;

data training;
set work.data_subset; *dataset in your work directory;
if selected = 1;
run;

data testing;
set work.data_subset; *dataset in your working directory;
if selected = 0;
run;

ods graphics on;
proc logistic data=work.training descending plots=roc;
class Gender /param = effect ref = first; *categorical variable;
model default = x1 x2 x3 x4 x5
/ link=logit;
score data=work.testing out=work.logisticOoutput;
run;
ods graphics off;

Using proc surveyselect to split the dataset 70% 30%, we can split our dataset into train and test. Then, we can run logistic regression on train data. see the performance on the test dataset.

score data=work.testing 

This command is running the regression on the test set. see the result in the output.

share|improve this answer

answered Apr 20 at 0:28

TomTom

91111

$endgroup$

proc surveyselect data=work.data method=srs seed=2 outall
samprate=0.7 out=work.data_subset;

data training;
set work.data_subset; *dataset in your work directory;
if selected = 1;
run;

data testing;
set work.data_subset; *dataset in your working directory;
if selected = 0;
run;

ods graphics on;
proc logistic data=work.training descending plots=roc;
class Gender /param = effect ref = first; *categorical variable;
model default = x1 x2 x3 x4 x5
/ link=logit;
score data=work.testing out=work.logisticOoutput;
run;
ods graphics off;

score data=work.testing 

share|improve this answer

answered Apr 20 at 0:28

TomTom

91111

answered Apr 20 at 0:28

TomTom

91111

answered Apr 20 at 0:28

TomTom

91111