What are two purposes of model nuggets? (Choose two.)

Question

Options

• AScoring data to generate predictions
• BEnabling further analysis of the model properties
• CMerging of two or more data sets
• DReducing the number of columns in a data set

• A
  8% (3)
• B
  89% (34)
• C
  3% (1)

Explanation

Model nuggets in IBM SPSS Modeler are the output objects generated after a modeling node runs. They serve two key purposes: (B) they let analysts inspect and interpret the model's internal properties - such as predictor importance, coefficients, accuracy metrics, and decision rules - and (D) certain nuggets (like Feature Selection) act as filters that reduce the number of input columns passed downstream, keeping only the most relevant fields.

Why A is wrong: Scoring (generating predictions on new data) is performed by placing the model nugget into a stream and running it against new data - it's a downstream application of the nugget, not a purpose of the nugget itself in this context. This exam distinguishes between what the nugget is versus what you do with it.

Why C is wrong: Merging datasets is the job of Merge or Append nodes, which combine records or fields from multiple sources - this has nothing to do with model nuggets.

Memory tip: Think of nuggets as "gold nuggets you mine and examine." You study their properties (B) and use them to sift out unnecessary material - i.e., trim columns (D). Scoring and merging are separate pipeline steps that happen around the nugget, not within it.

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