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Decision Tree for Boolean Functions in Machine Learning – 17CS73 Video Tutorial Decision Tree for Boolean Functions Machine Learning. Draw Decision Tree for logical Functions for the following functions. Solution: Every Variable in Boolean function such as A, B, C etc. has two possibilities that is True and False Every Boolean function is either True
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OR GATE Perceptron Training Rule – Artificial Neural Network in Machine Learning – 17CS73 Video Tutorial Truth Table of OR Logical GATE is, Weights w1 = 0.6, w2 = 0.6, Threshold = 1 and Learning Rate n = 0.5 are given For Training Instance 1: A=0, B=0 and Target = 0 wi.xi = 0*0.6 +
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AND GATE Perceptron Training Rule – Artificial Neural Network in Machine Learning – 17CS73 Video Tutorial Truth Table of AND Logical GATE is, Weights w1 = 1.2, w2 = 0.6, Threshold = 1 and Learning Rate n = 0.5 are given For Training Instance 1: A=0, B=0 and Target = 0 wi.xi = 0*1.2 +
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Gradient Descent Algorithm for Artificial Neural Networks in Machine Learning – 17CS73 Video Tutorial Gradient Descent and Delta Rule in ANN Gradient Descent and the Delta Rule is used separate the Non-Linearly Separable data. Weights are updated using the following rule, Where, Gradient Descent Algorithm Gradient descent is an important general paradigm for learning. It
