方法采用数据库及数据预处理技术。
Methods the data were analyzed with the database and data preprocessing technology.
基于多连续属性离散化的数据预处理方法。
A data preprocessing method based on multi continuous attribute discretization.
提出了一种基于散乱点云的数据预处理方法。
A method of data preprocessing based on scattered point cloud was proposed.
一是把数据预处理并转换成适当视图用以分析的所有操作。
One is all the preprocessing and transforming of the data into the proper view for analysis.
研究数据预处理过程，给出了关键技术和算法。
Studies the process of data preprocessing, gives the key technologies and algorithms.
数据预处理，数据压缩，特征选择与特征变换。
Data pre-processing, data reduction, feature selection, and feature transformation.
在数据预处理层对图形数据过滤、归整、修补。
Then, data is filtrated, consolidated and repaired in the preprocessing phase.
包括气象因子选取与数据预处理及人工神经网络模拟预报。
The rain forecast includes weather factor choosing, data pretreatment and manual network simulation forecast.
其次，对数据预处理与信息采集的方法与手段进行了探讨。
Secondly, it discussed the methods and means of data preprocess and collection.
其系统设计包括数据预处理、预售分析及预测分析模块设计。
The system includes data pretreatment, pre-sell analysis and forecasting analysis model.
对电磁场图形后处理技术进行了研究，给出了数据预处理画家算法。
Post processing techniques to electromagnetic field graph are studied and the Painter Algorithm with data preprocessing is given.
不同光谱数据预处理方法和谱区范围，影响建立定量分析模型的质量。
Different spectral data preprocessing methods and spectral regions have influences on the performance of model established.
本文首先研究了坐标变换、坐标归一化和数据滤波的数据预处理技术。
Firstly the data pre-processing technologies are researched, which include coordinate transform, coordinate fusion, data filtering.
知识发现的过程包括时间序列数据预处理、属性约简和规则抽取三部分。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
详细论述了在大型装配件逆向设计中三坐标测量及数据预处理的相关环节。
The related link of the three coordinate measuring and the data of pre-processing in reverse design of large assemble was discussed.
本文对基于粗集的数据预处理中数据补齐和连续属性离散化问题进行讨论。
This thesis discusses the question of data reinforce and continuous feature discretization which is based upon data preprocessing of rough set.
为提高少数类的分类性能，对基于数据预处理的组合分类器算法进行了研究。
In order to improve the performance of the minority class, a combined classifier algorithm is presented based on data pre - processing.
并强调了模型设计过程中要注意的数据提取、数据预处理、模型验证等问题。
And it emphasizes some questions in the model designing, such as data distilling, the pretreatment, model validating.
最后讨论了数据预处理的必要性，得到了一些对实际评估具有指导意义的结论。
Finally, data preprocessing's necessities is discussed and some conclusions are gained which have direct meaning to an actual evaluation.
近年来降维方法作为智能识别中关键的数据预处理技术得到了较为成功地运用。
Dimensionality reduction algorithms, as the key technologies of data preprocessing in intelligent recognition, have been used successfully recently.
此法以增加计算机内存为代价，获得对谱数据预处理的保序性及实时性的要求。
This method sacrifices the computer memory for the acquirement of the order preserving and real time of the spectral pretreatment.
对CRM数据挖掘过程的关键环节——数据预处理存在问题和算法进行了研究。
The key link of CRM data mining, problems and algorithm on data pre-processing, was researched.
主要讨论了如何利用改进的离散数据网格化方法快速实现离散地形数据预处理。
This thesis mainly discussed how to make use of the improved arithmetic of discrete data gridding to quickly realize discrete data pretreatment.
本论文主要讲述数据挖掘中采用粗糙集方法实现数据预处理中冗余属性约简的问题。
This paper mainly discusses topics on solving attribute reduction problems by applying rough set methods in the field of scientific data mining.
本文提出的商业数据挖掘系统包括数据准备层、数据预处理层、挖掘评价层三个层次。
The novel commercial data mining system presented in this paper include three parts: data preparation, data preprocessing, mining and evaluation.
区域化探资料处理主要是进行数据预处理、背景分析、相关场分析、多元统计分析等。
It is the region geochemistry pretreatment to pretreat the originality data and to analyze the background and correlation filed and statistics data.
数据预处理是KDD的关键一步，良好的数据预处理可以极大地提高数据挖掘的效率。
Preprocessing is a key step of KDD. Favorable preprocessing can improve efficiency of data mining.
然而，您将可能发现其更便于使用InfoSphereWarehouse内置数据预处理功能。
However, you will probably find it much more convenient to use the InfoSphere Warehouse built-in data preprocessing capabilities.
其基本环节有：模型表面空间坐标数据测量、数据预处理、重构曲面模型、数字模型输出。
Its basic step includes: data measure of model surface, points pretreatment, reconstruction surface model, and the digital model export.
其基本环节有：模型表面空间坐标数据测量、数据预处理、重构曲面模型、数字模型输出。
Its basic step includes: data measure of model surface, points pretreatment, reconstruction surface model, and the digital model export.
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