In a decision strategy, the Adaptive Model decision component belongs the
In a decision strategy, the Adaptive Model decision component belongs to the Decision Analytics category. This category contains components that use advanced analytics techniques, such as adaptive models, predictive models, text analytics models, etc., to make predictions or recommendations. Reference: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analytics-components
Which statement about the expected performance of a binary model is correct?
The expected performance of a binary model must be set before the model can be deployed.
U+ Insurance wants to use Pega Process Al to detect fraud and assign suspicious claims to a fraud expert for closer inspection.
To meet this requirement, how does an application developer use the outcome of a predictive fraud model in the case type that processes the incoming claim?
Pega Process AI lets you bring your own predictive models to Pega and use predictions in case types to optimize the way your application processes work and meet your business goals.
To use the outcome of a predictive fraud model in the case type that processes the incoming claim, you need to usethe model outcomeinthe condition of a decision step2. This way, you can route suspicious claims to a fraud expert for closer inspection based on the model's prediction.
The management team at U+ Insurance wants to improve the experience of dissatisfied customers. The customers send the feedback through email.
To detect the sentiment of the incoming emails, which type of prediction do you need to configure in Prediction Studio?
To detect the sentiment of the incoming emails, you need to configure atext analytics prediction1234in Prediction Studio. A text analytics prediction is a type of prediction that uses natural language processing (NLP) to analyze text data and extract insights, such as topics, entities, and sentiments. You can use a text analytics prediction to detect the sentiment of an email based on its content and assign a score ranging from -1 (negative) to 1 (positive). This can help you improve the customer experience by identifying dissatisfied customers and taking appropriate actions.
When building a predictive model, at what stage do you compare the performance of predictive models?
When building a predictive model, you compare the performance of predictive models at the Model Comparison stage. This stage allows you to select the best model based on various metrics, such as accuracy, lift, or area under curve (AUC). Reference: https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models
