![]() There are two types of algorithms you can use to train predictive models in ITSI: regression and classification. You decide to use the Last 90 days of data.įor help choosing an appropriate time period, see Specify a time period. Your last outage occurred two months ago, and you want to provide that data to the model so it can be trained on the difference between normal and abnormal data. ![]() You need to provide the model with enough data to capture the relationships that exist among the Middleware service's past KPI values and service health scores. You go to the Middleware service's Predictive Analytics tab to configure the training inputs. Now that you've decided to model the Middleware service, it's time to train a predictive model. With this even distribution, ITSI's machine learning models are less likely to produce biased results.īecause the Middleware service data contains no outliers and is evenly distributed, you determine that the Middleware service is a good fit for predictive modeling. You consult the histogram of service health scores and see that the distribution is fairly uniform (the data is spread evenly across the range of health scores). You look at the graph of service health scores and KPIs over time and see that the data is relatively cyclical with no obvious outliers. You set the time period on the Predictive Analytics tab to Last 14 days so you can get an idea of how the Middleware service's health scores have varied over the last two weeks. Step 1: Determine if the service is a good fit for modelingīefore you create a predictive model for the Middleware service, you want to make sure that the service is suitable for predictive modeling. Perform root cause analysis using the Predictive Analytics dashboard.Determine if the service is a good fit for modeling.This use case includes the following high-level tasks: To predict and avoid future outages, you want to create a machine learning model of the Middleware service using ITSI's Predictive Analytics capability. The Middleware service has experienced several costly outages in the past. You are an IT operations admin for the Middleware team. This example demonstrates how to use ITSI Predictive Analytics to build a machine learning model, and use the model to generate predictions that you can use to make business decisions. With ITSI Predictive Analytics, you can build and train predictive models and use them to create alerts.
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