<p>You could have one model for each type of service , which would predict the number of events in a given month and year based on history.</p>
<p>You could also jointly model them using a neural network to approximate the distribution or gaussian process.</p>

CC BY-SA 4.0
2022-02-04T19:18:32.897Z
2022-02-04T19:18:32.897Z
sma
<p>I have temporal data regarding the number of customers who requested a specific service in a given period (month and year). Below is a small excerpt from the dataset:</p>
<p><img src="https://i.sstatic.net/PpWqq.png" alt="1" /></p>
<ul>
<li>Month-year: month and year when the service has been requested/offered</li>
<li>Service Description: the tipology of the service request by the customer</li>
<li>occurences: how many times the customers in that period requested that service</li>
</ul>
<p>I have monthly data from 2003 to 2020 and I would like to carry out a predictive analysis to predict the number of events from 2021 to 2023 and also predict the type of services. For the first I know that I have to face the problem using the analysis of the time series, I have doubts about the second part ... how to predict the type of service in addition to the number of requests? Can you give me some suggestions?</p>

<long-short-term-memory><time-series><prediction>
time series analysis: predict number and type of service
Alfonso
# time series analysis: predict number and type of service

(Asked by: username_0 on 2022-02-03)

I have temporal data regarding the number of customers who requested a specific service in a given period (month and year). Below is a username_1ll excerpt from the dataset:

![1](https://i.sstatic.net/PpWqq.png)

* Month-year: month and year when the service has been requested/offered
* Service Description: the tipology of the service request by the customer
* occurences: how many times the customers in that period requested that service

I have monthly data from 2003 to 2020 and I would like to carry out a predictive analysis to predict the number of events from 2021 to 2023 and also predict the type of services. For the first I know that I have to face the problem using the analysis of the time series, I have doubts about the second part ... how to predict the type of service in addition to the number of requests? Can you give me some suggestions?

**Tags:** long-short-term-memory, time-series, prediction


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## 1 answers

### Answer by username_1 on 2022-02-04. Score: 0

You could have one model for each type of service , which would predict the number of events in a given month and year based on history.

You could also jointly model them using a neural network to approximate the distribution or gaussian process.


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