Natural Computation Methods for Machine Learning Note 11 Let us firstly revisit completive learning and SOFM Review CL and SOFM A node position (in the input space) is its weight vector, i.e. nodes move around in the same space as the data. Purpose of unsuperv…

2020年3月4日 0条评论 1823点热度 0人点赞 阅读全文

Natural Computation Methods for Machine Learning Note 10 In this note, we are going talk about Deep Learning very briefly. Radial Basis Function Networks RBFNs are feedforward networks, where: The hidden nodes (the RBF nodes) compute distances, instead of weig…

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Unsupervised Learning To learn from unlabeled data (only inputs, no target information). Most often for classification. Requires that class membership can be detected by structural properties (features) in the data, and that the learning system can be fund the…

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Natural Computation Methods for Machine Learning Note 08 ex) Tic-Tac-Toe Assign value to each board position (state): +1 if the state is a winning terminal state. 0 if the state is a losing terminal state +0.5 to all other states (terminal and non–terminal) pl…

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Natural Computation Methods for Machine Learning Note 07 From today, we are going to introduce reinforcement learning(RL). Forget ANNs for a while - RL is a field in its own right, independent from ANNs. However, as we will see, ANNs are sometimes used in RL. …

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Natural Computation Methods for Machine Learning Note 06 In this course, we learn more on extensions. and prior knowledge. Automatic dimensioning We want to minimize the number of hidden nodes(=> less overfitting) The approaches: start with a large networks an…

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Natural Computation Methods for Machine Learning Note 05 Let's continue talk about overtraining. Training set size The number of training set samples should be much larger than the number of weights roughly for ​ \(N^2\)(N = the number of weights). What to do …

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Natural Computation Methods for Machine Learning Note 04  Credit assignment problem in order to decide by how much of the result blamed or credited to a particular weight. We need sigmoid function. Sigmoid function = any S-shape function. examples. logistical …

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Natural Computation Methods for Machine Learning Note 03 Pattern recognition and the Perceptron This course, I learnt basic pattern recognition , perceptron and an overview of how to train/adjust the perceptron. Pattern recognition Here are some basic terms we…

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Neural basics A question, what is AI? Artificial Intelligence: It is not the art of making computers behave as they do in the movies. It is motivated by the brain, but do not overdo it. We always regard it as a black box.  After opening this box, we can see a …

2020年2月4日 0条评论 2666点热度 0人点赞 阅读全文
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