Machine Learning - Training and Testing - Training and Testing in Sklearn

Question

Machine Learning
Training and Testing
Training and Testing in Sklearn
We have 2d numpy array X of 100 datapoints and 4 features and 1d array y of 100 target values. What is the output of this code?
X_train, X_test, y_train, y_test = train_test_split(X, y)
print(X_train.shape, y_train.shape)
what i've tried :
1 already search the https://www.sololearn.com/Discuss and google but no enlight for this question
2 tested in jupyter notebook
pip install -U sklearn
import numpy as np
from sklearn.model_selection import train_test_split
X = np.array([[100], [4] ] )
y = np.array(100)
X_train, X_test, y_train, y_test = train_test_split(X, y)
traceback error
TypeError: Singleton array array(100) cannot be considered a valid collection.
my question :
how to get the result ?
( ___1___ , ___2___ ) ( ___3___ ,)
thanks

Answer 1

La réponse est : (75,4) (75,)
Je me suis basé sur l'exemple du cours pour trouver la réponse, par exemple dans le cours lorsqu'on avait 887 éléments on a eu comme résultat au shape 667 et 222 par défaut soit 222/887 = 0.25... donc 25% ce qui équivaut à 100-25 = 75 (qu'on peut trouver en faisant 667/887 aussi)

Answer 2

pip install -U sklearn
import numpy as np
from sklearn.model_selection import train_test_split
X = np.array([[100], [4] ] )
y = np.array([100] )
X_train, X_test, y_train, y_test = train_test_split(X, y)
traceback error
ValueError: Found input variables with inconsistent numbers of samples: [2, 1]

Answer 3

how to translate :
We have 2d numpy array X of 100 datapoints and 4 features and 1d array y of 100 target values.
into
python numpy, so that can test it on jupyter notebook ?
thanks

Answer 4

Result :
75,4,75

Answer 5

100 is an integer
Try this:
y = np.array([100]) 🤔

Answer 6

Ohh ya, the length of x and y should be same ig (dimensions also)

Answer 7

Result:
(75, 4) (75,)