CODEWITHSUNDEEP
pythontensorflowkeras
rnv86
rnv86

Reputation: 880

Data reshape with Keras and Jupyter

I'm trying to train a baseline ANN model for a binary classification with Keras (tensorflow backend) and Jupyter notebooks. The code is the following:

array=df6.values
X= array[:,0:384]
Y = array[:,385]

from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import StratifiedKFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline

seed = 7
np.random.seed(seed)
encoder = LabelEncoder()
encoder.fit(Y)
encoded_Y = encoder.transform(Y)

def create_baseline():
    model = Sequential()
    model.add(Dense(60, input_dim=60, kernel_initializer='normal', activation='relu'))
    model.add(Dense(10, kernel_initializer='normal', activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model

estimator = KerasClassifier(build_fn=create_baseline, epochs=100, batch_size=5, verbose=0)
kfold = StratifiedKFold(n_splits=2, shuffle=True, random_state=seed)
results = cross_val_score(estimator, X, encoded_Y, cv=kfold)
print("Baseline: %.2f%% (%.2f%%)" % (results.mean()*100, results.std()*100))

Finally the error is the following:

ValueError: Error when checking input: expected dense_5_input to have shape (None, 60) but got array with shape (8, 384)

Also my dataset has 18 rows and 385 columns I would like to know how to reshape correctly for a correct estimation of results. Thank you so much!

Upvotes: 0

Views: 267

Answers (1)

Daniel Möller
Daniel Möller

Reputation: 86600

input_dim = 384

This argument refers to the shape of your input, which is X.

Upvotes: 1

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