Suppose you have trained a perceptron algorithm on a binary classification problem using the following dataset: X1X2 Y 111 1-10 -110 -1-1 1 After training, the decision boundary of the perceptron is a straight line passing through the origin that separates the positive and negative examples. The activation function is (if v0. y-1: else y-0). Which of the following options represents the trained weights of this perceptron?

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
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Suppose you have trained a perceptron algorithm on a binary classification problem using the following dataset:
X1X2 Y
111
1-1 0
-110
-1-1 1
After training, the decision boundary of the perceptron is a straight line passing through the origin that separates the positive
and negative examples. The activation function is (if v-0. y-1: else y-0). Which of the following options represents the trained
weights of this perceptron?
Ow0-0, w1-1, and w2-1
Ow0-0, w1--1, and w2--1
OWO-1,w1-1, and w2-1
Ow0-1 w1--1, and w2--1
Transcribed Image Text:Suppose you have trained a perceptron algorithm on a binary classification problem using the following dataset: X1X2 Y 111 1-1 0 -110 -1-1 1 After training, the decision boundary of the perceptron is a straight line passing through the origin that separates the positive and negative examples. The activation function is (if v-0. y-1: else y-0). Which of the following options represents the trained weights of this perceptron? Ow0-0, w1-1, and w2-1 Ow0-0, w1--1, and w2--1 OWO-1,w1-1, and w2-1 Ow0-1 w1--1, and w2--1
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