3. (This exercise is a variation of Exercise 2.8 in Chapter 2 of the textbook) C

Question

3. (This exercise is a variation of Exercise 2.8 in Chapter 2 of the textbook) Consider the data as 2-D data points. Given a new data point x (1.4, 1.6) as a query, rank the database points based on the cosine similarity measure A2 x1 1.51.7 1.9 1.6 1.8 1.2 1.5 X2 2 X 1.5 In other words, find the cosine similarity for each data point and sort in decreasing order Similarity Closest Second closest Third closest Fourth closest Farthest Vector 4. (This exercise is a variation of Exercise 3.3 in Chapter 3 of the textbook) Using the data set given in Exercise 1 of this assignment, use smoothing by bin means to smooth this data, using a bin depth of 3 Round results to two decimal places Bins Smoothed by Bin Means

Explanation / Answer

I ALREADY ANSWERED THIS IF YOU HAVE ANY DOUBTS COMMENT BELOW

ANS:

We have given new data point X = c(1.4, 1.6)

Also we have given data set,

A1 A2

X1 1.5 1.7

X 2 2 1.9

X3 1.6 1.8

X4 1.2 1.5

X5 1.5 1

Now we compute a distance of each data point in given data set from the new data point X = c(1.4,1.6) using euclidian distance formula.

i.e. distance of X from X1 is sqrt((1.5-1.4)^2 + (1.7-1.6)^2) = 0.1414

distance of X from X2 is sqrt((2-1.4)^2 + (1.9-1.6)^2) = 0.6708

distance of X from X3 is sqrt((1.6-1.4)^2 + (1.8-1.6)^2) = 0.2828

distance of X from X4 is sqrt((1.2-1.4)^2 + (1.5-1.6)^2) = 0.2236

distance of X from X5 is sqrt((1.5-1.4)^2 + (1-1.6)^2) = 0.6083

Hence cosine similarity for each data point is,

Similarity Vector

Closest X1

Second CLosest X4

Third Closest X3

Fourth Closest X5

Fifth CLosest X2

THANK YOU

PLZZZZZZZZZZZZZZZZZZZZZZZZZZZZ RATE THUMBSUP

Related Questions

Navigate

• Browse (All)
• Browse 3
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.