| 1. | It sketches an outline of the data pattern more clearly .
它对资料模型的轮廓描绘得更清晰。 |
| 2. | Trigger on data patterns within a spi frame
在spi帧内的特定数据码型上触发在i |
| 3. | Trigger on address and or data patterns within an i2c frame
C帧内的特定地址和或数据上触发 |
| 4. | These numbers are sensitive to the data pattern of the existing data and of the data to be loaded
这些数字与现有数据及要加载的数据的数据样式相关。 |
| 5. | Commands to set data patterns , perform ecc tests , manipulate the error log , dump the sequencer ram
用来为测试配置柱面，磁头，给出选项来随机柱面/磁头和随机数据模式的指令。 |
| 6. | Spi triggering allows for trigger on user - definable framing and user - definable number of bits per frame , as well as data patterns
Spi允许在用户义帧,用户俯定义的每帧比特数以及数据码型上触发 |
| 7. | Simple , programmatically controlled xml or relational database getting and setting , is useful when only a trivial algorithm is required , but the data pattern is still too complex for datapool generated inputs
简单的说，当只需要一般演算法时，透过程式设计方法控制的xml或关联资料库的获取和设定是有用的，但资料样式对于产生的资料池输入仍旧是太复杂。 |
| 8. | In this paper , we propose a scheme to solve the problem of outlier data patterns that the value of outlier data pattern is deleted first and then is predicted by the model of genetic algorithm and neural network
对于数据集中的异常样本值，本文提出了一种解决方案：先删除异常的属性值，然后再用遗传bp神经网络模型进行预测填补，通过实验证明这种方案的可行性。 |
| 9. | It consists of demanding analysis , system structure , data flowing diagram , function module and the application of key techniques , takes and organizes offer parameter and data , uses entity - relation ( e - r ) pattern to design data pattern , selects ms sql server 7 as database , founds database physical structure
说明了基于c s和b s混合结构模式的设计与实现，包括系统的需求分析，系统的解决方案，系统的体系结构、数据流图、功能模块图以及各关键技术的应用。 |
| 10. | Discovering association rules is one of the most important task in data mining , that is to find interesting association or correlation relationships among a large set of data items . with massive amounts of data continuously being collected and stored , data patterns hidden in large data sets are more difficult to find
数据挖掘的一个重要的任务就是发现数据库中的关联规则，也就是发现数据项中项集之间有价值的关联或相关联系。随着大量数据不停地收集和存储，隐藏在数据项集中的数据模式也越来越难发现。 |
