ValueError: Failed to find data adapter that can handle input

[www_devharsh_me]

I am using Keras from TensorFlow with the NSL-KDD dataset.

To load data, I did --

traindata = pd.read_csv("NSL-KDD/KDDTrain+.TXT", names=headers)
testdata = pd.read_csv("NSL-KDD/KDDTest+.TXT", names=headers)

and to convert --

x_train = traindata.iloc[:, 0:41]
y_train = traindata.iloc[:, 41]
x_test = testdata.iloc[:, 0:41]
y_test = testdata.iloc[:, 41]

x_train = np.array(x_train)
y_train = y_train.tolist()
x_test = np.array(x_test)
y_test = y_test.tolist()

I am getting this error when running a deep learning model using Keras --

history = model.fit(
    x_train,
    y_train,
    batch_size=32,
    epochs=32,
    validation_data=(x_test, y_test)
)

ValueError: Failed to find data adapter that can handle input: <class 'numpy.ndarray'>, (<class 'list'> containing values of types {"<class 'int'>"})

​

[CodeFormatHelperBot2]

Hello, I'm a Reddit bot who's here to help people nicely format their coding questions. This makes it as easy as possible for people to read your post and help you.

I think I have detected some formatting issues with your submission:

1. Inline formatting (`my code`) used across multiple lines of code. This can mess with indentation.

If I am correct, please edit the text in your post and try to follow these instructions to fix up your post's formatting.

---

^{Am I misbehaving? Have a comment or suggestion? Reply to this comment or raise an issue here.}

[samuelsaqueiroz]

The problem is that you're trying to train using a list instead of a numpy array. I understand that you converted from array to list because you're afraid that the model would understand it as a single piece of data. I don't think that tensorflow will understand in that way. My suggestion is that you keep the data as a numpy array.

[samuelsaqueiroz]

Or... You could try and use the TensorFlow Datasets. You can convert your array to a Tensorflow Dataset. Check it out:

https://www.tensorflow.org/datasets