Analyzing example projects and models in Prediction Studio
Prediction Studio contains examples of predictive analytics projects, classification models, and sentiment models that are pre-installed. These projects are intended to be simple starting points to understand the functionality for each model type. You can access the example projects from the Predictions navigation panel.
You can use the pre-configured example projects to learn how to create and maintain different model types in various ways:
- You can Open an example to see how you configure an accurate and reliable model.
- You can Test and Run an example to learn how a correct model should operate and what results it should produce.
- You can Save a new instance of an example and use it as a baseline for your own model.
The following examples are available:
- Predict Prob of Default
- Scoring predictive analytics project.
- Predict Customer Value
- Spectrum predictive analytics project.
- Predict Credit Risk
- Extended scoring predictive analytics project. It requires an outcome inferencing license.
- Telecom taxonomy
- Topic detection model for the telecommunications industry.
- Banking taxonomy
- Topic detection model for the banking industry.
- Customer support taxonomy
- Topic detection model for customer support.
- Sentiment Models
- Default sentiment analysis model for multiple languages.
The DMSample application also includes the following example models:
- Predict Churn
- Predictive model with an associated project.
- Predict Risk
- Predictive model that uses a PMML model.
- Classify Call Context
- Text Classification model.
- Types of predictive models
Predictive models are optimized to predict different types of outcome.
- Prediction Studio overview
Prediction Studio is an authoring environment in which you can control the life cycle of AI and machine-learning models (such as model building, monitoring, and update). From Prediction Studio, you can also manage additional resources, such as data sets, taxonomies, and sentiment lexicons.