How to train single LSTM model on multiple independent data?
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I have to do time ahead prediction of memory and cpu utilization of different hosts in my IT infrastructure. For example, consider host1 having 2 columns of data for cpu and memery utilization for last 24 hours. similarly host2 have data for last 24 hours. Since data collected from different hosts has no relationship between them. I mean cpu and memory utilization of host1 has nothing to do with utilization on host2. Now, I want to train LSTM/RNN on this to predict next 24 hours utilization for both host1 and host2. How could I use single LSTM network to train on two different data set simultaneously? Is it possible to train lis this or do I require to train one LSTM model for host1 and other for host2? Kindly give suggestion.
deep-learning lstm
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I have to do time ahead prediction of memory and cpu utilization of different hosts in my IT infrastructure. For example, consider host1 having 2 columns of data for cpu and memery utilization for last 24 hours. similarly host2 have data for last 24 hours. Since data collected from different hosts has no relationship between them. I mean cpu and memory utilization of host1 has nothing to do with utilization on host2. Now, I want to train LSTM/RNN on this to predict next 24 hours utilization for both host1 and host2. How could I use single LSTM network to train on two different data set simultaneously? Is it possible to train lis this or do I require to train one LSTM model for host1 and other for host2? Kindly give suggestion.
deep-learning lstm
New contributor
$endgroup$
add a comment |
$begingroup$
I have to do time ahead prediction of memory and cpu utilization of different hosts in my IT infrastructure. For example, consider host1 having 2 columns of data for cpu and memery utilization for last 24 hours. similarly host2 have data for last 24 hours. Since data collected from different hosts has no relationship between them. I mean cpu and memory utilization of host1 has nothing to do with utilization on host2. Now, I want to train LSTM/RNN on this to predict next 24 hours utilization for both host1 and host2. How could I use single LSTM network to train on two different data set simultaneously? Is it possible to train lis this or do I require to train one LSTM model for host1 and other for host2? Kindly give suggestion.
deep-learning lstm
New contributor
$endgroup$
I have to do time ahead prediction of memory and cpu utilization of different hosts in my IT infrastructure. For example, consider host1 having 2 columns of data for cpu and memery utilization for last 24 hours. similarly host2 have data for last 24 hours. Since data collected from different hosts has no relationship between them. I mean cpu and memory utilization of host1 has nothing to do with utilization on host2. Now, I want to train LSTM/RNN on this to predict next 24 hours utilization for both host1 and host2. How could I use single LSTM network to train on two different data set simultaneously? Is it possible to train lis this or do I require to train one LSTM model for host1 and other for host2? Kindly give suggestion.
deep-learning lstm
deep-learning lstm
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asked 21 hours ago
VinayKrishnaVinayKrishna
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