I am trying for multi-class classification and here are the details of my training input and output: train_input.shape= (1, 95000, 360) (95000 length input array with each element being an array of 360 length) train_output.shape = (1, 95000, 22) (22 ...
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My input is simply a csv file with 339732 rows and two columns : the first being 29 feature values, i.e. X the second being a binary label value, i.e. Y I am trying to train my data on a stacked LSTM model: data_dim ...
Continuation from previous question: Tensorflow – TypeError: ‘int’ object is not iterable My training data is a list of lists each comprised of 1000 floats. For example, x_train[0] = [0.0, 0.0, 0.1, 0.25, 0.5, ...] Here is my model: model = Sequential() model.add(LSTM(128, activation='relu', ...