Whats true for principal component learning?(a) logical And & Or operations are used for input output relations(b) weight corresponds to minimum & maximumof units are connected(c) weights are expressed as linear combination of orthogonal basis vectors(d) change in weight uses a weighted sum of changes in past input valuesThe question was asked by my college professor while I was bunking the class.My query is from Learning Laws in section Activation and Synaptic Dynamics of Neural Networks

Whats true for principal component learning?(a) logical And & Or opera

1.	Whats true for principal component learning?(a) logical And & Or operations are used for input output relations(b) weight corresponds to minimum & maximumof units are connected(c) weights are expressed as linear combination of orthogonal basis vectors(d) change in weight uses a weighted sum of changes in past input valuesThe question was asked by my college professor while I was bunking the class.My query is from Learning Laws in section Activation and Synaptic Dynamics of Neural Networks
Answer» Right option is (C) weights are EXPRESSED as linear combination of orthogonal BASIS vectors To EXPLAIN: PRINCIPAL component learning involves weightsthat are expressed as linear combination of orthogonal basis vectors.

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