摘要:针对低压交流配电网中由于电弧燃烧程度不同、电流畸变程度不同而导致漏检、错检问题,提出一种基于Stacking模型融合的时域故障电弧检测方法。从回路电流中提取时域特征,将时域特征组成特征矩阵对机器学习算法决策树和集成学习算法随机森林等进行参数寻优。最后,将集成学习算法代替机器学习算法作为基学习器通过Stacking模型...
seed(seed) models <- caretList(Class~., data=dataset, trControl=control, methodList=algorithmList) results <- resamples(models) summary(results) dotplot(results) 1 2 3 4 5 6 7 8 9 SVM准确率最高,达到94.66%。[结果貌似不能复现啊?] 当使用stacking组合不同分类器时,我们希望不同分类器...
Keywords: injection molding;size prediction;whale optimization algorithm;Stacking ensemble learning;feature selection 引用本文: 陈忠杭,王舟挺,沈加明,等.基于WOA-Stacking集成学习的注塑产品尺寸预测[J].工程塑料应用,2024,52(6):135-141. (CHEN ...
stacked_test = np.concatenate([f.reshape(-1, 1) for f in input_test], axis=1) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 然后用第二层模型进行训练和预测 上述实现的完整代码见下面的链接 https:///WuLC/MachineLearningAlgorithm/blob/master/python/Stacking.py 如果错漏,欢迎交流指正 ###...
关键词：机器学习 Stacking 南海北部 海温预报 Abstract：In this paper, an efficient long-term SST forecast method is established based on Stacking (ET-ET) machine learning algorithm using reanalysis data of National Centers for Environmental Prediction and Mergid satellite and in situ data Global ...
基于Stacking集成学习算法的个人信用评估模型 Personal Credit Assessment Model Based on Stacking Ensemble Learning Algorithm 集成学习Stacking信用评估传统机器学习算法的预测精度往往依赖于具体的问题,集成学习通过综合若干基分类器的预测结果,实现了分类效果的显著提升.对集成学习的思想进行了简单地介绍,阐述了Stacking集成...
In this tutorial, you will discover the stacked generalization ensemble or stacking in Python. After completing this tutorial, you will know: Stacking is an ensemble machine learning algorithm that learns how to best combine the predictions from multiple well-performing machine learning models. The sc...
测试数据集为ionosphere 。可以从UCI Machine Learning Repository获得。这个数据集描述了大气中高能粒子的高频率天线返回的结果是否显示了结构。这个问题是一个二分类问题,共有351个样本,3个数值特征。 先载入数据集和和相关包 # Load libraries ...
(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=1, p=2, weights='uniform'), KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=1, p=2, weights='uniform')), 'k...
We present an analysis of a general machine learning technique called 'stacking' for the estimation of photometric redshifts. Stacking techniques can feed the photometric redshift estimate, as output by a base algorithm, back into the same algorithm as an additional input feature in a subsequent ...