Q1. Consider the neural network in Figure 25.13. Let bias values be fixed at 0, and let the weight matrices between the input and hidden, and hidden and output layers, respectively, be: W=(w1, w2, wz3) = (1, 1, –1) W = (w, w̟, w½)™ = (0.5, 1, 2)" Assume that the hidden layer uses RELU, whereas the output layer uses sigmoid activation. Assume SSE error. Answer the following questions, when the input is x = 4 and the true response is y =0: z1 w2 2 w3 23 Figure 25.13. Neural network for Q1.

Q1. Consider the neural network in Figure 25.13. Let bias values be fixed at 0, and let the weight matrices between the input and hidden, and hidden and output layers, respectively, be: W=(w1, w2, wz3) = (1, 1, –1) W = (w, w̟, w½)™ = (0.5, 1, 2)" Assume that the hidden layer uses RELU, whereas the output layer uses sigmoid activation. Assume SSE error. Answer the following questions, when the input is x = 4 and the true response is y =0: z1 w2 2 w3 23 Figure 25.13. Neural network for Q1.

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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