Let's train logistic regression (sklearn.linear_model.LogisticRegression(random_state=0)) on these 2 principal components and y labels to see how well our classes are separated on the plane. Question-: What accuracy_score do you get with logistic regression? Hint: train the model on train set and report accuracy on the test set this time. Use provided split in the cell below. xtr, xte, ytr, yte = train_test_split(digits_2d_pc, y, test_size=0.2, random_state=0)

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
icon
Related questions
Question

MNIST dataset

Handwritten digits from 0 to 9

digits = datasets.load_digits()
X, y = digits['data'], digits['target']

PCA

Now let's try to visualize MNIST with 2 PCA components

pca = PCA(n_components=2, random_state=0)
digits_2d_pc = pca.fit_transform(X)
 

Do you see any clusters?

Let's train logistic regression (sklearn.linear_model.LogisticRegression(random_state=0)) on these 2 principal components and y labels to see how well our classes are separated on the plane.

Question-: What accuracy_score do you get with logistic regression?

Hint: train the model on train set and report accuracy on the test set this time. Use provided split in the cell below.

xtr, xte, ytr, yte = train_test_split(digits_2d_pc, y, test_size=0.2, random_state=0)

# YOUR CODE HERE

 

PCA (n_components=2, random_state=0)
= pca.fit_transform (X)
рса %3D
digits_2d_pc
plt.figure(figsize=(10, 8))
plt.scatter(digits_2d_pc[:, 0], digits_2d_pc[:, 1], c=y)
plt.colorbar ()
plt.show()
30
8
20
-7
10
- 5
4
- 3
-10
2
-20
F1
-30
-30
-20
-io
10
20
30
Transcribed Image Text:PCA (n_components=2, random_state=0) = pca.fit_transform (X) рса %3D digits_2d_pc plt.figure(figsize=(10, 8)) plt.scatter(digits_2d_pc[:, 0], digits_2d_pc[:, 1], c=y) plt.colorbar () plt.show() 30 8 20 -7 10 - 5 4 - 3 -10 2 -20 F1 -30 -30 -20 -io 10 20 30
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps

Blurred answer
Recommended textbooks for you
Computer Networking: A Top-Down Approach (7th Edi…
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Concepts of Database Management
Concepts of Database Management
Computer Engineering
ISBN:
9781337093422
Author:
Joy L. Starks, Philip J. Pratt, Mary Z. Last
Publisher:
Cengage Learning
Prelude to Programming
Prelude to Programming
Computer Engineering
ISBN:
9780133750423
Author:
VENIT, Stewart
Publisher:
Pearson Education
Sc Business Data Communications and Networking, T…
Sc Business Data Communications and Networking, T…
Computer Engineering
ISBN:
9781119368830
Author:
FITZGERALD
Publisher:
WILEY