SOLO模型是对观察到的学习结果进行分类的理论框架，包括思维方式和复杂性水平两个关键特征。

SOLO model is a theory structure to classify the observed learning outcome with main features of models of thinking and levels of complexity.

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本文主要研究目前较为流行的基于统计学习理论的分类方法——支持向量机方法(SVM)，以及小波变换提取特征的方法，将其用于人脸检测。

This paper mainly make research on classify methods based on statistical theory, support vector machine (SVM), and feature extraction method-wavelet transform, and using them in human face detection.

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在统计学习理论中，尤其对于分类问题，VC维扮演着中心作用。

VC dimension plays a central role in the Statistical Learning Theory especially for classification problems.

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