Please answer the questions in the picture correctly, and it is done by a team of bartleby experts. Please don't copy paste the answer from the website, because it was my previous question. Not purely answered by a bartlely team expert, but rather taking Chegg's answer. So, please don,t copy paste solution from website. Because many answers from websites are inaccurate, as well as from Chegg [LO 5 & LO 6] Train by hand a single neuron using perceptron learningrules on the training set given below. Assume that all initial weightsincluding the bias of the neuron are zeros (0). Show the set of weightsincluding the bias at the end of each iteration. Use learning rate =1 andthe threshold function h(X) : threshold(net) = 1 if net >= 0;threshold(net) = 0 otherwise (pls check it out, textbook AIMA 3rdEdition pp. 723-724). Apply the examples in the given order and stopthe iteration by the time when you find the patterns are all correctlyclassified. Is the training set linearly separable, give your comment onExpl. NoOutputit.Input1001201111011140016101Learning Outcomes:LO 5: Apply various techniques to an agent when acting undercertaintyLO 6: Apply various AI algorithms to solve the problems

Answered: [LO 5 & LO 6] Train by hand a single…

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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Please answer the questions in the picture correctly, and it is done by a team of bartleby experts. Please don't copy paste the answer from the website, because it was my previous question. Not purely answered by a bartlely team expert, but rather taking Chegg's answer. So, please don,t copy paste solution from website. Because many answers from websites are inaccurate, as well as from Chegg

[LO 5 & LO 6] Train by hand a single neuron using perceptron learning
rules on the training set given below. Assume that all initial weights
including the bias of the neuron are zeros (0). Show the set of weights
including the bias at the end of each iteration. Use learning rate =1 and
the threshold function h(X) : threshold(net) = 1 if net >= 0;
threshold(net) = 0 otherwise (pls check it out, textbook AIMA 3rd
Edition pp. 723-724). Apply the examples in the given order and stop
the iteration by the time when you find the patterns are all correctly
classified. Is the training set linearly separable, give your comment on
Expl. No
Output
it.
Input
100
1
2
011
110
111
4
001
6
101
Learning Outcomes:
LO 5: Apply various techniques to an agent when acting under
certainty
LO 6: Apply various AI algorithms to solve the problems

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