The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a new one.
Which feature of MLOps lets you monitor the new model in the production environment without affecting the business outcomes?
This is because shadow mode allows you to test a new model in parallel with an existing model without affecting the decision outcomes. You can compare the performance of both models and decide whether to replace or keep the existing model.
Configuring an adaptive model involves selecting the potential predictors. How many potential predictors are recommended for an adaptive model?
Up to 100 fields to limit the impact on model speed Reference:
When configuring an adaptive model, it is recommended to select up to 100 potential predictors to limit the impact on model speed.
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). References: https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models
Proactive retention is applicable when a customer is
Proactive retention is applicable when a customer is likely to churn. Proactive retention is a strategy that aims to prevent customer attrition by identifying customers who are at risk of leaving and offering them incentives or solutions to retain them. Proactive retention requires predicting the customer’s churn risk and selecting the next best action accordingly. References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategies-/decisioning-strategies-proactive-retention/main.htm
What type of a predictor can you use in an adaptive model?
In an adaptive model, you can use Symbolic predictors.
Which two factors do you inspect to access the general health of the adaptive models in Prediction Studio? (Choose Two)
These factors indicate how accurate and explainable the models are, which are key measures of model health. The number of responses and decisions are related more to model usage rather than health.
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 a text analytics prediction1234 in 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 implementing a Next-Best-Action project, which step is recommended to be taken first?
When implementing a Next-Best-Action project, the recommended first step is to define Issue and Group hierarchy, which are used to organize and categorize propositions based on business objectives and customer needs. This step helps to align the project with the business vision and goals. References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
When selecting the list of predictors for an adaptive model you should
When selecting the list of predictors for an adaptive model you should consider properties from a wide range of sources. Predictors are properties that influence the customer behavior and can be derived from various sources such as customer profile, interaction history, proposition details, etc. References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-adaptivemodel/main.htm
The outcome of a scoring model indicates the likely
The outcome of a scoring model indicates the likely response to an offer that is presented to a customer. For example, a scoring model can predict if a customer will accept, reject, or defer an offer for a credit card upgrade. References: https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models
Pega Adaptive Models_________
Pega adaptive models learn about customer behavior in real time by analyzing the responses to each offer and updating their predictions accordingly. They do not require historical data, human effort, or inbound channels to function. References: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-models-overview
What two tasks does a system architect need to perform to export historical data? (Choose Two)
Two tasks that a system architect needs to perform to export historical data are export the data set and create a data set.
What is the difference between predictive and adaptive analytics?
The difference between predictive and adaptive analytics is that adaptive models use the customer data as predictors, while predictive models use the customer data as outcomes. Adaptive models learn from real-time customer interactions and update their predictions accordingly. Predictive models use historical customer data to train and validate their predictions. References: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-models-overview
What is the key component of a Next-Best-Action strategy?
The key component of a Next-Best-Action strategy is a strategy, which is a graphical representation of the business logic that determines which actions to offer to each customer and in what order. A strategy can use various components, such as business rules, predictive models, filters, prioritizers, etc., to achieve this goal. References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
Model transparency is becoming an important requirement for many businesses. In Prediction Studio, model transparency thresholds can be set for
In Prediction Studio, model transparency thresholds can be set for a model.
A contact center application recommends relevant actions for each customer. The business team wants to know the possible ways in which these actions can be ordered so that the contact center agent can discuss one proposition at a time, starting from the top.
As a strategy designer, what are your two options if you use a Prioritize component to order the actions? (Choose Two)
The prioritize component is used to order actions based on a numerical value, such as priority, propensity, or custom expression. You can choose to sort the actions in descending or ascending order. References: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/prioritizing-actions