Error when checking target: expected dense_2 to have shape (3,) but got array with shape (1,)

Question

I changed the data type but I could not resolve the error.

I tried One-Hot Encoding but it doesn't work too.

I don't know what's wrong:(

seed = 0
np.random.seed(seed)
tf.set_random_seed(seed)

df = pd.read_csv('HW01_dataset_tae.txt', sep=',' ,header=None, names = ["Native", "Instructor", "Course", "Semester", "Class Size", "Evaluation"])

dataset = df.values # dataframe to int64
X = dataset[:,0:5] # attribute
Y_Eva = dataset[:,5] # class 

e = LabelEncoder()
e.fit(Y_Eva)
Y = e.transform(Y_Eva)

K = 10 
kFold = StratifiedKFold(n_splits=K, shuffle=True, random_state=seed) 

accuracy = []

for train_index, test_index in kFold.split(X,Y):
    model = Sequential() 
    model.add(Dense(16, input_dim=5, activation='relu')) 
    model.add(Dense(10, activation='relu')) 
    model.add(Dense(3, activation='softmax'))
    model.compile(loss='mean_squared_error', 
              optimizer='adam', 
              metrics=['accuracy'])
    model.fit(X[train_index], Y[train_index], epochs=100, batch_size=2)

the error ; Error when checking target: expected dense_2 to have shape (3,) but got array with shape (1,)

is detected at here ; model.fit(X[train_index], Y[train_index], epochs=100, batch_size=2).

What shout I do?

pggsmiles pggsmiles · Accepted Answer · 2020-05-31T06:15:50

I solved the problem.

At this code,

model.fit(X[train_index], Y[train_index], epochs=100, batch_size=2)

the number of rows in 'Y[train_index]' must be three because the classes are three.

The error came out since each Y[train_index] has only one row.

So, I used One-Hot Encoding and changed the code like this.

e = LabelEncoder()
e.fit(Y_Eva)
Y = e.transform(Y_Eva)
Y_encoded = np_utils.to_categorical(Y) # changed code

K = 10 
kFold = StratifiedKFold(n_splits=K, shuffle=True, random_state=seed) 

accuracy = []

for train_index, test_index in kFold.split(X,Y):
    model = Sequential() 
    model.add(Dense(32, input_dim=5, activation='relu')) 
    model.add(Dense(16, activation='relu')) 
    model.add(Dense(3, activation='softmax'))
    model.compile(loss='categorical_crossentropy', 
              optimizer='adam', 
              metrics=['accuracy'])
    model.fit(X[train_index], Y_encoded[train_index], epochs=100, batch_size=2) # changed code

Finally, I was able to run the code.

Error when checking target: expected dense_2 to have shape (3,) but got array with shape (1,)

2 Answers