The study material to get Certified Pega Data Scientist 88V1 should be according to individual's learning style and experience. Real Pegasystems PEGACPDS88V1 Exam Questions certification makes you more dedicated and professional as it will provide you complete information required to work within a professional working environment. These questions will familiarize you with the PEGACPDS88V1 Exam Format and the content that will be covered in the actual test. You will not get a passing score if you rely on outdated practice questions.
The PEGACPDS88V1 exam is designed for data scientists who are seeking to validate their skills and knowledge in Pega technology. Pegasystems is a leading provider of customer engagement and operational excellence solutions, and this certification is recognized globally as a benchmark for expertise on the Pega platform.
Becoming a Pega Certified Data Scientist can open up many opportunities for professionals in the field of data science. It can enhance their credibility and increase their earning potential. It can also provide a competitive advantage in the job market, as more and more companies are looking for data scientists who have expertise in Pega technology.
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The Pegasystems PEGACPDS88V1 exam covers a wide range of topics, including data analysis, machine learning, data visualization, and data modeling. It is designed to test the skills required to develop predictive models, perform data analysis, and visualize data in meaningful ways. PEGACPDS88V1 exam also covers Pega-specific topics, such as the Pega Decision Management and Pega Customer Decision Hub, which are essential tools for data scientists working with Pega technology.
NEW QUESTION # 32
The Predictive Model Markup Language (PMML) allows for predictive models to
Answer: D
Explanation:
Explanation
The Predictive Model Markup Language (PMML) allows for predictive models to be easily shared between applications. PMML is a standard XML format that describes the input parameters, output score, and mathematical formulas of predictive models. PMML enables interoperability between different tools and platforms that support PMML, such as Pega Customer Decision Hub. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#data-/data-predictivemodel-/data-
NEW QUESTION # 33
Evidence an assessment of its viability, the Adaptive Model produces three outputs: Propensity, Performance and what is evidence in the context of an Adaptive Model? Performance and what is evidence in the context of an Adaptive Model?
Answer: D
Explanation:
Explanation
Evidence is the number of customers who exhibited statistically similar behavior to the current customer and responded to the modeled offer. It indicates how reliable the propensity score is based on the available data.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 34
A very important aspect of each model is how good a model or a given predictor is in predicting the required behavior. When building a predictive model, the use of testing and validation samples___________________
Answer: C
Explanation:
Explanation
A predictive model is a mathematical function that estimates the probability of an outcome based on input data. When building a predictive model, the use of testing and validation samples increases the accuracy of models123. Testing and validation samples are subsets of data that are used to evaluate how well a model performs on new data that was not used to train the model. Testing and validation samples help prevent overfitting, which is when a model learns too much from the training data and fails to generalize to new data.
NEW QUESTION # 35
Adaptive model components can output__________
Answer: D
Explanation:
Explanation
Adaptive model components can output the customer's propensity to accept an action. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 36
A large online store uses Pega Customer Decision Hub to smoothly adapt to changing customer behavior.
Adaptive models help accomplish this business objective as the models learn from customer responses.
Which statement about adaptive models is correct? s
Answer: D
Explanation:
Explanation
Adaptive models perform a binary model calculation. This means that adaptive models predict the likelihood of a positive or negative response for each action and customer profile. Adaptive models do not require underlying predictive models or historical data sets to start learning. They learn from customer responses in real time and continuously update their predictions. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
NEW QUESTION # 37
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