Given a vector of real numbers r = (r₁, r2, . . . , rn). We can convert this vector into a probability vector ‚ Pn) using the formulation: p¡ = e'¹/(Σï-₁ e¹¹), for all i. p = (P₁, P2, · Write a Python function vec_to_prob(r) that takes the vector r as input and returns the vector p. Both r and p will be numpy arrays. You can assume r is non-empty. Sample inputs and outputs: • Input: np.array([4, 6]), output: [0.11920292 0.88079708] • Input: np.array([3.4, 6.2, 7.1, 9.8]), output: [0.00151576 0.02492606 0.06130823 0.91224995] Hint: use numpy.sum [ ] # Write your function here Let's test your function. [ ] # Convert input from list to np.array first before calling your function to avoid errors print (vec_to_prob(np.array ( [4, 6]))) print (vec_to_prob (np.array( [3.4, 6.2, 7.1, 9.8]))) print (vec_to_prob(np.array([3, 5.5, 0])))

Given a vector of real numbers r = (r₁, r2, . . . , rn). We can convert this vector into a probability vector ‚ Pn) using the formulation: p¡ = e'¹/(Σï-₁ e¹¹), for all i. p = (P₁, P2, · Write a Python function vec_to_prob(r) that takes the vector r as input and returns the vector p. Both r and p will be numpy arrays. You can assume r is non-empty. Sample inputs and outputs: • Input: np.array([4, 6]), output: [0.11920292 0.88079708] • Input: np.array([3.4, 6.2, 7.1, 9.8]), output: [0.00151576 0.02492606 0.06130823 0.91224995] Hint: use numpy.sum [ ] # Write your function here Let's test your function. [ ] # Convert input from list to np.array first before calling your function to avoid errors print (vec_to_prob(np.array ( [4, 6]))) print (vec_to_prob (np.array( [3.4, 6.2, 7.1, 9.8]))) print (vec_to_prob(np.array([3, 5.5, 0])))

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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