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• What is true regarding adaline learning algorithm(a) uses gradient descent to determine the weight vector that leads to minimal error(b) error is defined as MSE between neurons net input and its desired output(c) this technique allows incremental learning(d) all of the mentionedThis question was addressed to me during an online interview.My doubt stems from Analysis of Feature Mapping Network in division Competitive Learning Neural Networks of Neural Networks
• Use of nonlinear units in the feedback layer of competitive network leads to concept of?(a) feature mapping(b) pattern storage(c) pattern classification(d) none of the mentionedI have been asked this question during an online interview.Query is from Analysis of Feature Mapping Network in chapter Competitive Learning Neural Networks of Neural Networks
• In self organizing network, how is layer connected to output layer?(a) some are connected(b) all are one to one connected(c) each input unit is connected to each output unit(d) none of the mentionedThis question was posed to me during an interview for a job.My query is from Analysis of Feature Mapping Network topic in chapter Competitive Learning Neural Networks of Neural Networks
• What is true for competitive learning?(a) nodes compete for inputs(b) process leads to most efficient neural representation of input space(c) typical for unsupervised learning(d) all of the mentionedThis question was addressed to me in an online interview.My query is from Analysis of Feature Mapping Network topic in section Competitive Learning Neural Networks of Neural Networks
• In feature maps, when weights are updated forwinning unit and its neighbour, which type learning it is known as?(a) karnaugt learning(b) boltzman learning(c) kohonen’s learning(d) none of the mentionedI got this question in exam.I would like to ask this question from Analysis of Feature Mapping Network topic in division Competitive Learning Neural Networks of Neural Networks
• How are weights updated in feature maps?(a) updated for winning unit only(b) updated for neighbours of winner only(c) updated for winning unit and its neighbours(d) none of the mentionedI got this question in class test.I'm obligated to ask this question of Analysis of Feature Mapping Network topic in chapter Competitive Learning Neural Networks of Neural Networks
• What kind of learning is involved in pattern clustering task?(a) supervised(b) unsupervised(c) learning with critic(d) none of the mentionedThe question was posed to me during an interview for a job.My question is taken from Analysis of Feature Mapping Network topic in division Competitive Learning Neural Networks of Neural Networks
• How is feature mapping network distinct from competitive learning network?(a) geometrical arrangement(b) significance attached to neighbouring units(c) nonlinear units(d) none of the mentionedThe question was asked in an interview for job.The question is from Analysis of Feature Mapping Network in division Competitive Learning Neural Networks of Neural Networks
• What is the objective of feature maps?(a) to capture the features in space of input patterns(b) to capture just the input patterns(c) update weights(d) to capture output patternsThis question was posed to me in unit test.I want to ask this question from Analysis of Feature Mapping Network in chapter Competitive Learning Neural Networks of Neural Networks
• In competitive learning, node with highest activation is the winner, is it true?(a) yes(b) noThis question was addressed to me by my college professor while I was bunking the class.Enquiry is from Feedback Layer in section Competitive Learning Neural Networks of Neural Networks