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Time series forecasting using deep learning with 2 numFeatures

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How to use two input features to get 1 output using this example?
This example use 1 numFeatures, for example if i have time series data with 2 features, wind speed and temperature, how can i use this example to forecast weather?

Accepted Answer

Anshika Chaurasia
Anshika Chaurasia on 30 Sep 2020
Hi Israt,
It is my understanding that you have two features as input and want to train the network with this input.
You could change numFeatures = 2 while defining sequenceInputLayer function as shown:
numFeatures = 2; %take 2 features as input
numResponses = 1; %give 1 output
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits)
fullyConnectedLayer(numResponses)
regressionLayer];
  2 Comments
israt fatema
israt fatema on 29 Oct 2020
Thank you for the response. In this case how can i read and load the time series data with these two features such as wind speed and temperature?
The example contains a single time series, the output is a cell array, where each element is a single time step and then reshaped the data to be a row vector.
israt fatema
israt fatema on 12 Feb 2021
Hi, the Matlab example https://au.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html read 1 (one feature). I couldn't read more than 1 feature from the dataset (timeseries) if i want to use numFeatures = 2
%data = chickenpox_dataset;
%data = [data{:}];
How to read more than 1 (for example numFeatures = 2 and output = 1) feature from the dataset to get 1 output?
Thanks in advance.

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