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。
It involves statistics, profiling and pattern recognition, behavioral analysis, time series analysis, predictive modeling, visualization, cause-and-effect studies and more.
它涉及到统计，分析和模式识别，行为分析，时间序列分析，预测建模，可视化，因果的研究等等。
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。
Support Vector Machine (SVM) is an intellectual learning method based on the statistics theory. The SVM can solve problems of complicated nonlinear pattern recognition of spatial samples.
支持向量机(SVM)是基于统计学习理论的一种智能学习方法，可以用来解决样本空间的高度非线性的模式识别等问题。
The most important thing here is to understand image processing, it requires a broad level of knowledge including, some math (algrebra, statistics, PDE), dsp, pattern recognition, programming skills…
图象其实就是信号处理，除了本科是学信号的以外，信号与系统、数字信号处理是一定要学好的，那相应的数学方面的概率，多元统计，甚至泛函也要了解。
The most important thing here is to understand image processing, it requires a broad level of knowledge including, some math (algrebra, statistics, PDE), dsp, pattern recognition, programming skills…
图象其实就是信号处理，除了本科是学信号的以外，信号与系统、数字信号处理是一定要学好的，那相应的数学方面的概率，多元统计，甚至泛函也要了解。
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