Those against include the mine operators and the many who work in the mines; mining salaries are, on average, Australia's highest, according to the Australian Bureau of Statistics.
而反对者包括矿业主和在矿区工作的人员；澳国家统计局数据显示，矿业的平均收入是澳大利亚所有行业中最高的。
The field is closely related to data mining and often USES techniques from statistics, probability theory, pattern recognition, and a host of other areas.
此领域与数据挖掘密切相关，并且经常需要使用各种技巧，包括统计学、概率论和模式识别等。
Finally, I want to reiterate that this article and the ones in the future parts of this series only are a brief introduction to the field of statistics and data mining.
最后，我再重申一下，本文及本系列的后续文章只是对数据统计和数据挖掘领域做了最简单的介绍。
Historically, data mining has been a task that could only be accomplished by experts in statistics and data analysis.
在过去，数据挖掘一直是统计和数据分析专家的任务。
Data mining is a hotspot that combines the techniques in databases, artificial intelligence and statistics areas.
数据挖掘融合了数据库技术、人工智能和统计学，是目前的研究热点。
This paper analysis a variety of ventilating systems adopted in the coal face in mining coal of our country by using the method of statistics and compares their advantages and the range available.
本文用统计分析法介绍和分析了我国煤炭开采中，采煤工作面采用的各种通风系统并对比其优点和适用范围。
Do you want to find out how statistics and machine learning can save you time and effort mining text?
你想知道统计学和呆板进修在开掘文本方面能够让你省时省力的因为吗？
At present, outlier data mining is a hotspot for the researchers of database, machine learning and statistics.
目前，离群挖掘正逐渐成为数据库、机器学习、统计学等领域研究人员的研究热点。
Data Mining is a new technology which appeared in recent years. It combines with machine learning, statistics, database and many other fields' technologies.
数据挖掘是近年来出现的一种综合了机器学习、统计学、数据库等众多领域的新技术。
Classification is one of the most basic tasks during the biological statistics and data mining.
在生物统计以及数据挖掘中，分类预测是最基本的任务之一。
Data mining is an intercrossed subject, involving many fields such as machine learning, model reorganization, induction and deduction, statistics, database and high performance calculation.
数据挖掘是一门交叉性学科，涉及机器学习、模式识别、归纳推理、统计学、数据库、高性能计算等多个领域。
In this paper we discuss this problem in detail and put forward a method of mining positive and negative temporal correlation based on statistics.
该文对这类问题进行了详细的讨论，提出了一种基于统计方法的正负时态相关性挖掘算法。
Quantitative analysis of the surface movement induced by mining of underground useful deposit should be made based on the reliable data obtained by using the probability statistics method.
文中针对地下矿床开采引起的地表移动问题，提出了采用概率统计的方法来对地表移动进行定量分析，为地表变形分析提供了可靠的数据。
It is a practical meaning that forecast intelligently and statistics quickly data in the electric material system to save money and economize labour force by the technology of the Data Mining.
对电力物资系统的物资出库数据进行数据挖掘，有利于智能预测、快速数据统计，具有节省人力、财力的现实意义。
In the first stage, according to the enterprise's own characteristic and need, some apt to received statistics indexes has been chosen to screen to the supplier by taking data mining method.
第一阶段采用神经网络数据挖掘方法，针对企业自身特点和需要，选择一些易得到的统计数据指标选取。
Last, in discussing the relation of Data Mining and statistics, the sameness and distinguish between them are given.
最后对数据挖掘与统计学的关系进行了讨论，指出了数据挖掘与统计学相同之处和本质区别。
Data mining techniques have their origins in methods from statistics, pattern recognition, databases, artificial intelligence, high performance and parallel computing and visualization.
数据挖掘技术起源于从统计方法，模式识别，数据库，人工智能，高性能和并行计算和可视化。
Researchers are getting more and more attentions to cluster analysis, since it involved in many fields such as statistics, data mining, machine learning and image processing, etc.
聚类分析涉及到统计学、数据挖掘、机器学习和图像处理等多个领域，人们对它研究热情日益高涨。
Association rules can find some correlation info between these fields. By use of statistic techniques of data mining we can draw exact and plain statistics reporting from the chaotic and massive data.
关联规则能发现数据中的属性字段之间的相关性，利用数据挖掘中的统计技术我们可以从纷繁杂乱的海量数据中得出条理清晰的统计数据报表。
Used of the data statistics, data mining, model analysis and other methods, mainly deal with the following two questions:1. Multi-attribute associations (select) problem.
研究中主要用到了数据统计法、数据挖掘法、模型分析法等多种方法，主要解决以下两个问题：1、多属性关联（查询）问题。
Used of the data statistics, data mining, model analysis and other methods, mainly deal with the following two questions:1. Multi-attribute associations (select) problem.
研究中主要用到了数据统计法、数据挖掘法、模型分析法等多种方法，主要解决以下两个问题：1、多属性关联（查询）问题。
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