C1000-059 Exam Dumps - IBM Data and AI: Data and AI Questions and Answers

Cup of Vectors

Box of Lexicon

Sack of Sentences

Bag of Words

for skewed data

for real numbers

for normally distributed data

for large data sets

persona

snapshot

My Sticky Note

user summary report

Naive Bayes can be used for regression.

Let p(C1 | x) and p(C2 | x) be the conditional probabilities that x belongs to class C1 and C2 respectively, in a binary model, log p (C1 | x) – log p(C2 | x) > 0 results in predicting that x belongs to C2.

Naive Bayes is a conditional probability model.

Naive Bayes doesn't require any assumptions about the distribution of values associated with each class.

standard deviation = 0.5

expected value = 0

expected value = 0.5

expected value = 1

standard deviation = 1

division by random numbers

square

logarithm

subtract median

Test the newly trained model.

Document the errors from the built in models.

Obtain image files containing objects to be classified and organize them into classes.

Use IBM SPSS to create new machine learning classifiers.

64 inches and 74 inches

66.5 inches and 69 inches

71.5 inches and 76.5 inches

66.5 inches and 71.5 inches