Natural Computation Methods for Machine Learning Note 12 From course, I learned Evolutional Computing. Evolutionary computing (EC) population method Used for problems where the task is to maximize some measure of success Same family of problems as in RL, but v…
Hello everyone! 这篇文章将介绍Dice coefficient以及其实现 Introduction Dice coefficient 是 Lee R. Dice 在1945年为评估生物种群提出的一种度量方法[1]。后来不同领域的学者都将其引入到自己的专业。这里，我将介绍Dice codfficient 在图像分割领域作为评价指标的理解与实现。 Segmentation 图像分割包含有语义分割、示例分割。在语义分割中，我们需要对给定的图片做如下处理： - 标记出所有属于背景类别的点。 - 标记出属于我…
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…
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…
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…
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…
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. …
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…
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 …
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 …
