Ch. 10

Question 1

K-nearest neighbors algorithm

Answer 1

You get a new data point
Look at its X nearest neighbors
Classify the new data point based on its nearest neighbors

Question 2

Normalization exa

Answer 2

Look at a users average rating ie 3.3 and raise or lower their ratings a little until they reach an average value ie 3.5

Question 3

Classification

Answer 3

Categorization into a group

Question 4

Regression

Answer 4

Predicting a response (like a number)

Question 5

Cosine similarity

Answer 5

An alternative to the distance formula that compares the angles of vectors

Question 6

OCR

Answer 6

Optical character recognition
Having a computer recognize characters off a page ie scanning a book

Question 7

What do ocr algorithms typically measure

Answer 7

Lines
Points
Curves

Question 8

Training

Answer 8

The first phase of ocr where you go through images of numbers and extract features

Question 9

Naive Bayes Classifier

Answer 9

Spam filters
Break a sentence into words to estimate the probability of a word appearing in a spam email

Question 10

Feature

Answer 10

An aspect of data you will compare. Ie size, color, weight, a numeric rating etc.