Question

An adaptive model captures outcomes of ____________.

A) similar propositions
B) only positive customer responses
C) a subset of customer responses
D) only negative customer responses

Answer 1

A) similar propositions

An adaptive model is designed to capture outcomes of similar propositions, learning from a broad range of data inputs to improve predictive accuracy. These inputs include both positive and negative customer responses.

Step-by-step explanation:

An adaptive model captures outcomes of similar propositions. This type of model is designed to adjust based on feedback from a wide range of outcomes, not limited strictly to positive or negative responses. The intent of such a model is to learn from all inputs to enhance the accuracy and effectiveness of predictions or decisions. In this context, similar propositions refer to outcomes that are grouped because of their resemblances in certain characteristics or circumstances.

Examples of Adaptive Models:

• Machine learning algorithms that predict customer behavior based on diverse data inputs, both positive and negative.
• Adaptive models in climate science that update predictions based on a range of climate data and simulations.

In predictive analytics and decision-making processes, an adaptive model's strength is its ability to incorporate a wide array of data and adjust in response to how the environment changes.

Answer 2

An adaptive model in business captures the outcomes of similar propositions, including both positive and negative correlations and integrating retrospective and prospective analyses to refine strategies.

Step-by-step explanation:

An adaptive model in business contexts captures outcomes of various propositions or scenarios to adjust strategies or operations. The correct answer to the question is A) similar propositions. An adaptive model does not solely focus on positive or negative customer responses, nor does it only consider a subset of responses. Instead, it typically looks at a range of possible outcomes based on different scenarios, which can include positive correlation, negative correlation, retrospective analysis of past data, or prospective predictions about future trends.

For example, in analyzing marketing strategies, an adaptive model might incorporate both the successful engagements (positive correlations) and the unsuccessful ones (negative correlations) to optimize future campaigns. Additionally, these models can incorporate both retrospective (past outcomes) and prospective (future predictions) elements to refine the strategies used in business.