I am using CNN-LSTM network for image classification. My image size is (224, 224, 3) and batch size is 90. I m getting this error when i passing input to LSTM l
I have a data frame that looks like the one below: DF.head(20): time var1 var2 prob 12:30 10 12 85 12:31 15
I'm working on a RNN model to recognize speech keywords. I found out that the code below need to run at least 5 minutes in google colab. Is there any way of cod
Hi Im currently working on the below program but im getting below error: ValueError: Input 0 of layer "sequential_35" is incompatible with the layer: expected s
I'd like to use a LSTM network on Tensorflow to implement a difference equation. I searched on internet but I didn't find anything about this topic. The equatio
I am trying to predict a simple pattern using LSTM based network. I input a single vector and get the output vector with the same shape as a prediction. How can
The HAR dataset should be analyzed using LSTM and 1D CNN. I need to check the graph of the change in loss and check the confusion matrix. I don't know how to ma
I am training the coarse-to-fine coreference model (for some other language than English) from Allennlp with template configs from bert_lstm.jsonnet. When I rep
I am trying to use Keras for an attention mechanism in a machine translation using an LSTM network. However, I get a TypeError exception when in my code. TypeEr
I'd like to train a simple LSTM model for sequence data with 128 time steps with 6 features for 118 multi-classes. The dimensions of the dataset are shown belo
I am having a use case where I need to predict n number of future values after using the given data. eg: I have data from Jan 1 2021 - Jan 1 2022. I need to pre
I know that in ai models lstm is used to extract features from data and dropout is used to focus in the main ones, but i can't understand why people used to rep
When I try to fit my model i get an error. Here is the code: model = Sequential() model.add(LSTM(128, activation='relu', input_shape=(trainX.shape[1], trainX.sh
I am doing a project on an online signature verification system using RNNs LSTM. In the project, I am facing a problem while using the signatures as LSTM trai
I am trying to identify the important features in a data frame containing stock data. I plan on using LSTM to predict closing prices later on. I currently have
I currently have an LSTM which uses sequence length as input, but this only allows the LSTM to predict when the input length is equal to the used sequence lengt
I have a task for my project paper and I do not get how to train the model. This model is supposed to take an image and segment it into different classes. The h
I am trying to code a K-fold cross validation with LSTM architecture. But I got an this error (edit): Traceback (most recent call last): File "/Users/me/Deskt
I try to use Functional API for my model, but i don't understand why i have error: ValueError: Shapes (128, 100) and (128, 100, 139) are incompatible My code:
enter image description here model = Sequential() model.add(LSTM(units=32, return_sequences=True, input_shape=(training.shape[1],1))) model.add(Dropout(0.2)) mo