• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Artificial Intelligence and Pattern Recognition >Issues on critical objects in mining algorithms
【24h】

Issues on critical objects in mining algorithms

机译：矿业算法中的关键对象问题

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Data objects are considered as fundamental keys in learning methods that without the objects the mining algorithms are meaningless. Data objects basically direct the accuracy of the selected algorithm in case if they are extracted from inappropriate groups. Knowing the exact type of data object leads the miner to provide a suitable environment for learning algorithms. Supervised and unsupervised learning methods propose some membership functions that perform with respect to behaviour of each data category to classify data objects and solutions. The paper explores different type of data objects by categorizing them based on their behaviour with respect to learning methods. We also introduce some critical objects that play the main role in each data set. Issues on critical objects in mining algorithms are fully discussed in this paper. The accuracy and behaviour of these critical objects are compared by running fuzzy, probabilistic, and possibilistic algorithms on some data sets presented in this paper. The results prove that some methods are able to provide a suitable environment for critical objects and some are not. The comparison results also show that most of the learning methods have difficulties dealing with critical objects. Lack of ability to deal with these objects may cause irreparable consequences.
机译：数据对象被视为学习方法中的基本键，没有挖掘算法没有对象毫无意义。数据对象基本上引导所选算法的准确性，以防他们从不适当的组中提取它们。了解数据对象的确切类型导致矿工提供合适的学习算法环境。监督和无监督的学习方法提出了一些隶属函数，这些函数对于对每个数据类别的行为进行分类，以对数据对象和解决方案进行分类。本文通过根据其行为对学习方法进行分类来探讨不同类型的数据对象。我们还介绍了一些在每个数据集中播放主要角色的关键对象。本文完全讨论了采矿算法中的关键对象问题。通过在本文呈现的一些数据集上运行模糊，概率和可能性算法来比较这些关键对象的准确性和行为。结果证明了一些方法能够为关键对象提供合适的环境，有些方法是没有。比较结果还表明，大多数学习方法都有困难处理关键对象。缺乏应对这些物品的能力可能会导致无法修复的后果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号