That takes us to an important point that I wanted to secretly and slyly get across to everyone: Sometimes applying a data mining algorithm to your data will produce a bad model.
这也是我想审慎地告诉大家的一点：有时候，将数据挖掘算法应用到数据集有可能会生成一个糟糕的模型。
The algorithm makes use of the clustering technology of data mining, can apply to general radar and special radar.
这种算法利用了数据挖掘中的聚类技术，可用于常规雷达和特殊雷达的信号分选。
This thesis mainly discusses how to classify the potential customers with data mining algorithm and technology, by which there can be a correct orientation in the process of practical work.
本文主要讨论如何在信用卡一级代理过程中运用数据挖掘算法和技术对潜在客户进行分类，以便能在开展业务的过程中有所针对性。
This paper proposes a rough spectral clustering algorithm and apply the algorithm on text data mining.
该文提出了一种粗糙谱聚类算法，并将其应用于文本数据挖掘。
This essay is researching the Decision Tree Algorithm of Data Mining and the use in the Customer Drain analysis.
本文主要是研究数据挖掘中的决策树算法以及决策树算法在具体的小灵通流失分析中的研究与分析。
When mining large databases, the data extraction problem and the interface between the database and data mining algorithm become become issues.
对大型数据库进行数据开采时，数据抽取问题及数据库和开采算法的接口设计就变得十分重要。
It summarizes the main features of every algorithm by analyzing and comparing a variety of typical classifiers to provide a basis for selecting or improving the algorithms in data mining.
通过对当前数据挖掘中具有代表性的优秀分类算法进行分析和比较，总结出了各种算法的特性，为使用者选择算法或研究者改进算法提供了依据。
Most data mining tools use rule discovery and decision tree technology to extract data patterns and rules; its core is the inductive algorithm.
大部分数据挖掘工具采用规则发现和决策树分类技术来发现数据模式和规则，其核心是归纳算法。
This article proposes a data sorting method via the EM algorithm, for the purpose of mining high-quality decisions by performing data reasoning in a database with incomplete, noisy and uncertain data.
针对存在不完整、含噪声和不确定数据的数据库，通过挖掘高质量的决策，对数据库的数据进行推理，提出了一种基于EM算法的数据清理方法。
The key link of CRM data mining, problems and algorithm on data pre-processing, was researched.
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 algorithm can be directly applied to data mining, digital grid partitioning and estimation, data partitioning, digital terrain surface simplification, etc.
实现的算法可以直接应用于数据挖掘、数字网格划分与评估、数据分割、数值地形曲面的简化等问题。
Data mining adopts the improved ID3 algorithm and can meet the demand of load analysis and prediction.
数据挖掘采用改进ID 3算法，能够满足负荷分析和预测方面的要求。
There are some various algorithms in data mining, and decision tree classification algorithm is the most popular one.
在数据挖掘中存在多种算法，决策树分类算法是应用比较多的一种。
Finally, the experimental results illustrate the improved KFCM algorithm can achieve good clustering performance and high efficiency for software engineering data mining.
实验结果表明，改进的KFCM算法对软件工程数据的挖掘有很好的聚类效果，且有较高的效率。
It is a necessary part of data mining of data pretreatment that cleaning and inducing data and providing object data for classification algorithm.
数据预处理是数据挖掘中不可或缺的一部分，是对数据进行初步地清理和归纳，为分类算法提供目标数据。
This thesis presents data mining aided signature automatic discovery algorithm for network based IDS and detection rule creation algorithm.
提出了基于数据挖掘的网络入侵检测规则特征值自动发现算法和规则自动生成算法。
Data classification is an important task of data mining, and developing high-powered classification algorithm is one of the key problems for data mining.
数据分类是数据挖掘中的一个重要课题，研究各种高效的分类算法是数据挖掘的重要问题之一。
Facing the massive volume and high dimensional data, how to build effective and scalable algorithm for data mining is one of research directions of data mining.
面对大规模、高维的数据，如何建立有效的，可扩展的分类数据挖掘算法是数据挖掘研究的重要方向之一。
The paper describes the concepts and relationship of BI and data mining briefly, and introduces the popular data mining algorithm.
对商务智能、数据挖掘的概念和两者的关系做了简要的描述，并对当前流行的数据挖掘算法做了介绍。
Facing the massive volume and high dimensional data how to build effective and scalable clustering algorithm for data mining is one of research directions of data mining.
面对大规模的、高维的数据，如何建立有效、可扩展的的聚类数据挖掘算法是数据挖掘领域的一个研究热点。
Clustering algorithms are the typical algorithms in the data mining, the K-means algorithm is the most basic algorithm, which has produced many classics and highly effective algorithms.
聚类是数据挖掘中的典型算法，其中的K -均值算法是最基本的算法，由该算法产生了许多经典而高效的算法。
This thesis presents a data generalization algorithm based on data cube. The algorithm can clean the data for data mining and im-prove efficiency of data mining.
该文提出了一种基于数据立方体的数据泛化算法用于数据预处理，能够为数据挖掘提供良好的数据环境，提高数据挖掘的有效性。
The key idea of mining association rules for the basket data is studied and several methods to improve algorithm efficiency and rules selection are given.
对零售业销售数据关联规则挖掘算法的关键思想进行了研究，给出了各种提高算法效率的方法以及对规则选择的方法。
This paper illustrates the basic concepts of data mining and in detail discusses the Algorithm C5 approach for data mining.
本文介绍了数据挖掘的基本概念，重点分析了决策树C5算法。
For multi-relational data mining, how mining more efficiently and how improving the scalability of the algorithm, has been the focus of our study.
对于多关系的数据挖掘研究，如何高效地挖掘以及如何提高算法的可扩展性，一直是大家研究的重点。
The third involves data experiment of mining algorithm on historical operating data of a 600mw unit for one month, and analysis of mining results under different conditions.
第三部分针对某600MW机组一个月的历史运行数据进行模式挖掘算法的数据实验，并分析了不同工况下的挖掘结果。
Results The decision tree algorithm ID3 and C4.5 for medical image data mining are realized, the experiment results are given.
结果实现了ID3和C4.5算法对图像数据的分类，获得了分类的实验结果。
The search space of Multi-relational data mining algorithm becomes larger and more complex.
多关系数据挖掘算法的搜索空间变得更大、更复杂。
The search space of Multi-relational data mining algorithm becomes larger and more complex.
多关系数据挖掘算法的搜索空间变得更大、更复杂。
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