Now, we'll instead use sklearn 's train_test_split function instead. Store train data into X_train and train labels into Y_train . Similarly, store tes data into X_test and test labels into Y_test. We will use the following arguments for this task: • test_size : 0.2 • random_state : random_state (variable defined at the start) I # YOUR CODE HERE raise NotImplementedError() I assert X_train.shape == (6400, 200e) assert X_test.shape == (1600, 2000) assert Y_train.shape == assert Y_test.shape == (1600, ) (6400, )
Now, we'll instead use sklearn 's train_test_split function instead. Store train data into X_train and train labels into Y_train . Similarly, store tes data into X_test and test labels into Y_test. We will use the following arguments for this task: • test_size : 0.2 • random_state : random_state (variable defined at the start) I # YOUR CODE HERE raise NotImplementedError() I assert X_train.shape == (6400, 200e) assert X_test.shape == (1600, 2000) assert Y_train.shape == assert Y_test.shape == (1600, ) (6400, )
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Using python
![Now, we'll instead use sklearn 's train_test_split function instead. Store train data into X_train and train labels into Y_train . Similarly, store test
data into X_test and test labels into Y_test .
We will use the following arguments for this task:
• test_size : 0.2
random_state : random_state (variable defined at the start)
I # YOUR CODE HERE
raise NotImplementedError()
I assert X_train.shape
assert X_test.shape == (1600, 2000)
== (6400, 2000)
assert Y_train.shape
assert Y_test.shape ==
== (6400,)
(1600,)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3200e892-7b83-4670-8aa5-c4c84f2a6adb%2F5c4c631e-94f4-4af9-8204-6970f32e8ec4%2Fmaxmqxm_processed.png&w=3840&q=75)
Transcribed Image Text:Now, we'll instead use sklearn 's train_test_split function instead. Store train data into X_train and train labels into Y_train . Similarly, store test
data into X_test and test labels into Y_test .
We will use the following arguments for this task:
• test_size : 0.2
random_state : random_state (variable defined at the start)
I # YOUR CODE HERE
raise NotImplementedError()
I assert X_train.shape
assert X_test.shape == (1600, 2000)
== (6400, 2000)
assert Y_train.shape
assert Y_test.shape ==
== (6400,)
(1600,)
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