Time series forecasting using deep learning with 2 numFeatures

2020 9 15
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更新时间：2021 2 12
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How to use two input features to get 1 output using this example?
https://au.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html
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?

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Anshika Chaurasia
Anshika Chaurasia 2020-9-30

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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];

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israt fatema
israt fatema 2020-10-29
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 2021-2-12
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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