Pass the SAS Institute Natural Language and Computer Vision Specialist A00-405 Questions and answers with CertsForce

µ and o^2 are estimated using an exponentially weighted average across tram and test sets

Normalizations are applied using parameters learned during testing

Normalizations are applied using parameters learned during training

µ and o^2 are estimated using an exponentially weighted average across test set

misspelling detection

synonym list

minimum number of documents

start list

More proper nouns terms than the pronouns terms are kept

There are 9 concepts in total

There are 2 custom concepts

Most preposition terms are kept

When a Concept node appears after a Text Parsing node, only kept terms derived by the Text Parsing node can be used in concept creation

When a Concept node is placed after a Text Parsing node: the term table is affected by the concepts defined in the Concept node and the concepts impact every node that follows the Concept node

When the Concept node appears before the Text Parsing node in the pipeline, the spell-checking features of the Concept node produce parent and child terms that show up as synonyms in the term table created by the Text Parsing node

When a Concept node is placed before a Text Parsing node the term table is affected by the concepts defined in the Concept node and the concepts impact every node that follows the Text Parsing node

Sigmoid

ReLU

TanH

Softmax

Simple Random Sampling

Systematic Sampling

Stratified Random Sampling

Latin Hypercube Sampling

The term relevancy score ranges front 0 to 1.

A custom topic assigns a term relevancy score of 1 to each document containing the term.

You can split or merge topics

A single document contains only one topic