What is the translation of " 数据挖掘技术 " in English?

data mining techniques
数据 挖掘 技术
data mining technique
数据 挖掘 技术
with data mining technologies

Examples of using 数据挖掘技术 in Chinese and their translations into English

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数据挖掘技术和应用:介绍本月发表。
Data Mining Techniques and Applications: An Introduction was published this month.
利用数据挖掘技术,收集的数据可以用来分析。
With data mining technologies the collected data can be used for analysis.
数据挖掘技术广泛使用OLAP应用程序。
Data mining techniques widely accept OLAP applications.
数据挖掘技术和应用程序:介绍在本月出版。
Data Mining Techniques and Applications: An Introduction was published this month.
然而,NLP和NLU是许多其他数据挖掘技术的对立面。
NLP and NLU are opposites of a lot of other data mining techniques.
但是,NLP和NLU是许多其他数据挖掘技术的对立面。
NLP and NLU are opposites of a lot of other data mining techniques.
分类是一种重要的机器学习和数据挖掘技术
Classification is an important machine learning and data mining technology.
数据挖掘技术用于许多研究领域,包括数学,控制论,遗传学和营销。
Data mining techniques are used in many research areas, including mathematics, cybernetics, genetics, and marketing.
分类是一种数据挖掘技术,它将类别分配给数据集合,帮助更准确地预测和分析。
Classification is a data mining technique that assigns categories to a collection of data in order to aid in more accurate predictions and analysis.
有些人可能使用数据挖掘技术,而另一些人则更喜欢数学模型。
Some might use data mining techniques while others prefer a mathematical model.
分类是一种数据挖掘技术,为数据分配类别以帮助进行更准确的预测和分析。
Classification is a data mining technique that assigns categories to a collection of data in order to aid in more accurate predictions and analysis.
这本书,数据挖掘技术和应用:引言,是首开先河,其主要从计算相关学科的本科目标读者。
The book, Data Mining Techniques and Applications: An Introduction, is the first of its kind that primarily targets undergraduate readers from computing-related disciplines.
对于每种数据挖掘技术,我们将在比较解决每种问题所用的各种策略之前,研究目前新的佳实践。
For each data mining technique, we will review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem.
数据挖掘技术,包括数据库系统中,数据挖掘技术在图像的应用和生物数据,人机交互和视觉语言。
Data mining techniques, including database systems, the application of data mining techniques in image and biological data, human-computer interaction and visual languages.
分类是一种数据挖掘技术,它将类别分配给数据集合,帮助更准确地预测和分析。
Classification is a data mining technique that assigns categories to a collection of data to aide in more accurate predictions and analyses.
在本教程中,我们将会探索如何使用数据挖掘技术收集Twitter的数据,这可能会比你想象中的更有用。
In this tutorial,we will be exploring how we can use data mining techniques to gather Twitter data, which can be more useful than you might.
分类是一种数据挖掘技术,可让我们预测数据实例的组成员身份。
Classification is a data mining technique that lets us predict group membership for data instances.
并且我希望你能够积极参与尝试和编程数据挖掘技术
I hope you will be actively involved in trying out andprogramming data mining techniques.
分类是一种数据挖掘技术,它将类别分配给数据集合,以助进行更准确的预测和分析。
Classification is a data mining technique that assigns categories to a collection of data to aide in more accurate predictions and analyses.
然后在此基础上,你将构建几个完整的模型,包括线性和非线性模型,学习数据挖掘技术
Then, building on this foundation, you will construct several complete models, both linear and nonlinear,and use some data mining techniques.
分析师,研究人员,科学家,学生和所有想要获得使用SPSS包并学习流行数据挖掘技术的人。
Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package andlearn popular data mining techniques.
你将能够构建概率分布,对你的数据应用各种统计测试,并使用标准的机器学习和数据挖掘技术
You will be able to build probability distributions, apply a variety of statistical tests to your data,and use standard machine learning and data mining techniques.
为了打印此类模型,研究人员采用数据挖掘技术,分析了最影响表面自清洁特性的打印参数。
To print such models, the researchers used data mining techniques to analyze the printing parameters that most affected the surface's self-cleaning characteristics.
为了打印此类模型,研究人员采用数据挖掘技术,分析了最影响表面自清洁特性的打印参数。
To create these models, by means of data mining techniques, they analyzed the printing parameters that most influence self-cleaning features on surfaces.
真正的数据科学家通过将核心科学和突破性数据挖掘技术与难以理解的人类理解艺术相结合来解决这个问题。
True Data Scientist solves the problem by combining the hardcore science andbreakthrough data mining technologies with the inexplicable art of human understanding.
相似性和相异性被许多数据挖掘技术所使用,如聚类、最近邻分类、异常检测等。
Similarity andDissimilarity are important because they are used by a number of data mining techniques, such as clustering, nearest neighbour classification, and anomaly detection.
特别报告员还建议各国不要为反恐目的开发和使用数据挖掘技术
The Special Rapporteur also recommends against the development and use of data-mining techniques for counter-terrorism purposes.
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