Answers.Body: <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>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-02-04T19:18:32.897Z
Answers.LastActivityDate: 2022-02-04T19:18:32.897Z
Answers.UserDisplayName: sma
Body: <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>
  
Tags: <long-short-term-memory><time-series><prediction>
Title: time series analysis: predict number and type of service
UserDisplayName: Alfonso
ThreadText: # 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 small 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
  
  
  ---
  
  ## 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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