Predicts whether a customer will change providers (denoted as churn) based on the usage pattern of customers. Predicts whether the firewall is going to be affected by malware or has a vulnerability or not based on various traffic indicators on the firewall. Predicts whether the hard drive is going to fail based on various indicators of drive reliability. A common use of these predictions is to identify anomalies: predictions that differ significantly from the actual value may be considered anomalous. Predict the value of a categorical field using the values of other fields in that event. Predict future VPN usage with categorical time data. Predict Future VPN Usage (categoricall time) Predict future VPN usage with sinusodial time data. Predict Future VPN Usage (sinusodial time) Predict future logins in business process. Predicts the power output of the power plant given other measured variables, such as ambient temperature and humidity.īusiness processes (cyclical_business_process.csv) Predicts median home value in a region based on housing value-related predictor fields.
Predicts the VPN usage of employees based on the frequency of use of other apps. Predicts the power usage of a machine based on other metrics such as CPU utilization and memory transactions. Predict the value of a numeric field using a weighted combination of the values of other fields in that event. Predicts vulnerabilities in firewall data from other fields in the data including bytes received, packets received, packets sent, and bytes sent. Predicts disk utilization from the fields of disk access and disk blocks. Predict the value of a categorical or numeric field based on one or more other fields in the event using a step-by-step guided workflow. The Showcase contains the following examples, grouped here by Assistant type. You can use these datasets to practice machine learning concepts, or to re-create the Showcase examples in your own instance before working with your own data. MLTK ships with all of the example datasets used in the Showcase. Industry options include IT, Security, Business Analytics, IoT, Health, and Finance. Machine learning operation options include Predict Fields, Detect Outliers, Forecast Time Series, and Cluster Events. Filter the available Showcases by machine learning operation or industry to see the examples that best match your machine learning goals. Each end-to-end example is comprised of a pre-populated use case for the Machine Learning Toolkit and each of the guided modeling Assistants. Use the Machine Learning Toolkit (MLTK) Showcase to explore machine learning concepts.
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