[Solved] What is the output of this code?import numpy as np from scipy import special x = np.array([0, 1, 2]) y = special.expit(x) print(y) | SciPy

SciPy - Basics and Scientific Computing

What is the output of this code?

import numpy as np
from scipy import special
x = np.array([0, 1, 2])
y = special.expit(x)
print(y)

A[0.5 0.73105858 0.88079708]

B[1. 2. 7.3890561]

C[0. 1. 2.]

D[0. 0.5 0.75]

Step-by-Step Solution

Solution:

Step 1: Understand special.expit function
special.expit computes sigmoid 1 / (1 + exp(-x)): sigmoid(0)=0.5, sigmoid(1)≈0.73105858, sigmoid(2)≈0.88079708 matching [0.5 0.73105858 0.88079708].
Final Answer:
[0.5 0.73105858 0.88079708] -> Option A
Quick Check:
sigmoid([0,1,2]) = [0.5 0.73105858 0.88079708] [OK]

Quick Trick: expit = sigmoid function, check values at 0,1,2 [OK]

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