实验中主要选择了K均值聚类算法、FCM模糊聚类算法并以UCI Machine Learning Repository网站下载的WINE数据集为基础,然后以WINE数据集在学习了解Weka软件接口方面的基础后作聚类分析,使用最常见的K均值(即K-means)聚类算法和FCM模糊聚类算法。下面简单描述一下K均值聚类的步骤。 K均值算法首先随机的指定K个类中心。然后:...
The data was downloaded from UCI Machine Learning Repository. The two datasets are related to red and white variants of the Portuguese "Vinho Verde" wine. For more details, the reference [Cortez et al., 2009]. Due to privacy and logistic issues, only physicochemical (inputs) and sensory ...
UCI数据集下载:UCI Machine Learning Repository: Wine Quality Data Set 数据集下载:White Wine Quality | Kaggle White Wine Quality白葡萄酒品质数据集的使用方法 ML之回归预测之Lasso:利用Lasso算法对红酒品质wine数据集实现红酒口感评分预测(实数值评分预测) M...
Experiments are conducted using the Red Wine and White Wine datasets from UCI Machine Learning Repository. The results showed that the proposed quality estimation framework using IPCA and ICSA-FNN has higher performance than the existing models in terms of accuracy, precision and computation time.Ali...
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UCI数据集下载:UCI Machine Learning Repository: Wine Quality Data Set 数据集下载:White Wine Quality | Kaggle White Wine Quality白葡萄酒品质数据集的使用方法 ML之回归预测之Lasso:利用Lasso算法对红酒品质wine数据集实现红酒口感评分预测(实数值评分预测) ...
Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) tests. In this paper, we propose a data mining
was donated into the UCI repository [1]. The data contain 178 examples with measurements of 13 chemical constituents (e.g. alcohol, Mg) and the goal is to classify three cultivars from Italy. This dataset is very easy to discriminate ...
Newman. UCI Machine Learning Repository, University of California, Irvine, http://www.ics.uci.edu/?mlearn/MLRepository.html, 2007. [2] J. Bi and K. Bennett. Regression Error Characteristic curves. In Proceedings of 20th Int. Conf. on Machine Learning (ICML), Washington DC, USA, 2003. ...
These data are the results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines.