CODEWITHSUNDEEP
pythontensorflowkerasneural-network
siiddd
siiddd

Reputation: 53

Error when checking input: expected input_18 to have 3 dimensions, but got array with shape (7, 210)

My Original Dataset is of the shape (210,8) and I'm trying to give the 7 Independent Variables as Input to my Neural Network to see which Class/Category they belong to. The Class/Category is the Target Variable.

I have separated the independent variables and stored them in 'df_test' as an array

df = pd.read_csv('https://raw.githubusercontent.com/siiddd/WheatSeeds/master/Wheat.csv')

features = ['Area', 'Perimeter', 'Compactness', 'Length of Kernel','Width of Kernel', 'Asymmetric Coeff.', 'Length of Kernel Groove']

dftoArray = df[features].to_numpy()
df_test = dftoArray.reshape(7,210)

model = keras.Sequential()

model.add(keras.Input(shape = (7, )))

model.add(keras.layers.Dense(500, activation = 'relu'))
model.add(keras.layers.Dense(1, activation = 'sigmoid'))

model.compile(optimizer = 'adam', loss = 'sparse_categorical_crossentropy', metrics = ['accuracy'])

model.fit(df_test, df['Class'], epochs = 10, validation_split = 0.10)

This gives me the error:

Error when checking input: expected input_18 to have 3 dimensions, but got array with shape (7, 210)

Upvotes: 2

Views: 62

Answers (1)

Shubham Panchal
Shubham Panchal

Reputation: 4289

I think you are making a mistake while reshaping the DataFrame. As you said, the data consists of 210 samples each having 8 features i.e the shape of the data must be ( 210 , 8 ). Now, after selecting the desired columns from the df you need to reshape your data to ( 210 , 7 ) and not ( 7 , 210 ). Make this change,

df_test = dftoArray.reshape( 210 , 1 )

Shapes ( 210 , 7 ) and ( 7 , 210 ) have a huge difference. The shape ( 7 , 210 ) refers to a dataset which consists of 7 samples with 210 features each. This is not the case.

Upvotes: 1

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