源码文件
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decision 源代码
决策技术（Decision）是现代电子系统设计中不可或缺的一环，广泛应用于自动化控制、人工智能及数据分析等领域。通过高效算法与模型，Decision技术帮助工程师实现复杂系统的智能优化与管理。掌握这一技能，不仅能够提升项目开发效率，还能增强解决方案的灵活性与可靠性。本站提供77个…
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源码文件
.EN .TH C4.5 1 .SH NAME .PP consult \- classify items using a decision tree .SH SYNOPSIS .PP .B consult [ \fB-f\fR FNS ] [ \fB-t\f…
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function [D, w] = LS(train_features, train_targets, weights, region) % Classify using the least-squares algorithm % Inputs: %…
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function D = Nearest_Neighbor(train_features, train_targets, Knn, region) % Classify using the Nearest neighbor algorithm % In…
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function D = Perceptron_BVI(train_features, train_targets, params, region) % Classify using the batch variable increment Percep…
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function D = Minimum_Cost(train_features, train_targets, lambda, region) % Classify using the minimum error criterion via histo…
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function D = Perceptron_Batch(train_features, train_targets, params, region) % Classify using the batch Perceptron algorithm %…
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function D = None(train_features, train_targets, Params, region) % Make no classifications (Dummy function) % Inputs: % feat…
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function [decision, P] = Bayesian_Belief_Networks(net, data) % Find the most likely decision given a Bayesian belief network an…
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function D = ML(train_features, train_targets, AlgorithmParameters, region) % Classify using the maximum-likelyhood algorithm …