I chose the best alpha and lambda values for three different analyses (so I have three different models). My predictors are ordinal, and my outcome is binary. I have selected the best models (two being ridge) and trained them on the training data. I know that I need to predict the models on the test data, but I'm really confused on how to do this with binarized data. See the latter of my code below:

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#For analysis one, select best alpha and lambda values and create model

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#Split predictor variables and DV and convert to as.matrix

train_predictors_1 <- as.matrix(train.data1[ ,-(1)])

test_predictors1 <- as.matrix(test.data1[ ,-(1)])

train_dv1 <- as.matrix(train.data1$state)

test_dv1 <- as.matrix(test.data1$state)

#Develop chosen model - chose binomial family due to binary outcome variable

A1_en <- glmnet(train_predictors_1, train_dv1, family = "binomial", alpha = 0.1, lambda = .05) #Elnet

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#For analysis two, select best alpha and lambda values and create model

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#Split predictor variables and DV and convert to as.matrix

train_predictors_2 <- as.matrix(train.data2[ ,-(1)])

test_predictors2 <- as.matrix(test.data2[ ,-(1)])

train_dv2 <- as.matrix(train.data2$state)

test_dv2 <- as.matrix(test.data2$state)

#Develop chosen model - chose binomial family due to binary outcome variable

A2_en <- glmnet(train_predictors_2, train_dv2, family = "binomial", alpha = 0, lambda = .2) #Ridge

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#For analysis three, select best alpha and lambda values and create model

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#Split predictor variables and DV and convert to as.matrix

train_predictors_3 <- as.matrix(train.data3[ ,-(1)])

test_predictors_3 <- as.matrix(test.data3[ ,-(1)])

train_dv3 <- as.matrix(train.data3$state)

test_dv3 <- as.matrix(test.data3$state)

#Develop chosen model - chose binomial family due to binary outcome variable

A3_en <- glmnet(train_predictors_3, train_dv3, family = "binomial", alpha = 0, lambda = .15) #Ridge

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#Look at coefficients

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#Model 1

enet.coef_1 <- coef(A1_en, lambda = .05, alpha= .1, exact=T)

#Model 2

enet.coef_2 <- coef(A2_en, lambda = .2, alpha = 0, exact=T)

#Model 3

enet.coef_3 <- coef(A3_en, lambda = .15, alpha = 0, exact=T)

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