数据采掘的英文
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"数据采掘"怎么读用"数据采掘"造句
英文翻译手机版
- data excavating
- data mining
- "数据"英文翻译 data; record; information
- "采掘"英文翻译 digging; hewing; cutting; ex ...
- "数据开发,数据采集,数据采掘," 英文翻译 : data mining
- "数据采集" 英文翻译 : acquisition, data; da data acquisition; dacq; data acquistion; data aquisition; data capture; data collection; data gathering; data logging
- "数据采集板" 英文翻译 : data acquisition board
- "数据采集架" 英文翻译 : dac data acquisition chassis
- "数据采集卡" 英文翻译 : data acquisition board; pcl-725 pcl-818l
- "数据采集器" 英文翻译 : data acquisition unit; data acquisitor; data trap; datac
- "数据采集网" 英文翻译 : data acquisition network
- "数据采集站" 英文翻译 : das data acquisition station; data collection station
- "数据采样" 英文翻译 : sampling
- "数据采样率" 英文翻译 : data sampling rate
- "元数据采集" 英文翻译 : metadata acquisition
- "并行数据采集" 英文翻译 : parallel data acquisition
- "串行数据采集" 英文翻译 : serial data acquisition
- "地理数据采编" 英文翻译 : geographical data handling
- "地面数据采集" 英文翻译 : surface data acquisition
- "多路数据采集" 英文翻译 : multi-channel data acquisition
- "分散数据采集" 英文翻译 : decentralized data acquisition
- "高速数据采集" 英文翻译 : high-speed data acquisition; hsda high speed data acquisition
- "管理数据采集" 英文翻译 : management data collection
- "海上数据采集" 英文翻译 : offshore acquisition
- "联机数据采集" 英文翻译 : on-line data acquisition
- "三维数据采集" 英文翻译 : 3-d data collection; three dimensional data collection
- "数据采集板卡" 英文翻译 : data-acquisition boards
例句与用法
- With the boom of date mining , bayesian network has been paid great attention and again in the limeligh < because of the naturai relation between the mathematical statistics and data mining
由于概率统计与数据采掘的天然联系。数学采据兴起后贝叶斯网络日益受到重视,再次成为引人注目的热点 - Therefore , it is the same with data mining with probability statistic character and knowledge discovery problems , especially with die problems that obtain sample information or need high cost
因此,适用于具有概率统计特征的数据采掘和知识发现问题,尤其是样本难以获取或代价过于昂贵的问题。 - Comparing with non - bnyain methods , it ' s prominent featares lay in that it combines the prior and posterior information , which avoids the disadvantag of subjective bias caused by simply using the prior information only , of blind search caused by the incomplete sample information , of noise affection caused by simply using the sample information only if we choice a suitable priof , we can conduct the bayesian leaming effectively , so it fits the problems of data mining and machine leaming that possess charaters of probability and statistics , especially when the samples are rare
与非贝叶扬方法相比,贝叶斯方法的特出特点是其学习机制可以综合先验信息和后验信息,既可避免只使用先验信息可能带来的主观偏见,和缺乏样本信息时的大量盲目搜索与计算,也可避免只使用样本信息带来的噪音的影响只要合理地确定先验,就可以进行有效的学习。因此,适用于具有概率统计特征的数据采掘和机器学习(或发现)问题,尤其是样本难得的问题
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