…用 TeX 标记表示：N.\ R.\ Draper and H.\ Smith, {\it Applied Regression Analysis,\/} John Wiley and Sons, New York, 1968.\ \ Leo Breiman, Jerome H.\ Friedman, Richard A.\ Olshen, Charles J.\ Stone, {\it Classification and Regression Trees,\/} ISBN 0-534-98054-6, Wadsworth \& Brooks/Cole, Pacific Grove, California, 1984.\ \ C.\ Radhakrishna Rao, {\it Linear Statistical Inference and Its Applications:\ \ Second Edition,\/} ISBN 0-471-70823-2, John…
…with TeX markup: N.\ R.\ Draper and H.\ Smith, {\it Applied Regression Analysis,\/} John Wiley and Sons, New York, 1968.\ \ Leo Breiman, Jerome H.\ Friedman, Richard A.\ Olshen, Charles J.\ Stone, {\it Classification and Regression Trees,\/} ISBN 0-534-98054-6, Wadsworth \& Brooks/Cole, Pacific Grove, California, 1984.\ \ C.\ Radhakrishna Rao, {\it Linear Statistical Inference and Its Applications:\ \ Second Edition,\/} ISBN 0-471-70823-2, John…
…SVM（支持向量机）本质上是一种曲线拟合的应用，跟经典多元统计里的判别分析（discriminate analysis）有关。它与树模型的联系，大概很像 Breiman 等人的《Classification and Regression Trees》（CART）里的那种，那是应用统计学的一部经典著作。Breiman 曾是一位出色的数学家、概率学家兼应用统计学家。Machine Learning 跟人类学习或心理学意义上的学习完全是两码事。这门课看起来…
…(support vector machines) is an application of curve fitting related to discriminate analysis in classic multi-variate statistics. The connections with trees are likely much as in the Breiman, et al., Classification and Regression Trees (CART), a classic in applied statistics. Breiman was a good mathematician, probabilist, and applied statistician. Machine Learning is nothing like learning in humans or psychology. The course looks…
…普通回归要是效果不灵，那我就不太愿意硬去折腾更复杂的玩意儿了。在某些情况下，我可能还愿意试试 L. Breiman（我很尊敬 Breiman，他是 Loeve 的学生）在他的《Classification and Regression Trees》里写的那套东西。
…ordinary regression doesn't work very well, then I'm reluctant to strain with much more. I might be willing in some circumstances to use what L. Breiman (I respect Breiman, Loeve student) has in his Classification and Regression Trees.
…尤其是，掌握的程度要足以理解回归就是正交投影（perpendicular projection），从而再次把勾股定理给串起来。要想进一步了解面向机器学习的这类统计学，去搞一本 Breiman 的 CART——《Classification and Regression Trees》，这大概算得上 ML 的很大一部分源头。学了这么多统计学，你见过的应用概率论就相当多了，可能可以去啃真家伙了。为此，你需要懂测度论，比如前半部分的…
…particular, get enough to understand that regression is a perpendicular projection and, thus, get the Pythagorean theorem again. For more on such statistics aimed at machine learning, get the Breiman CART -- Classification and Regression Trees, maybe much of the start of ML. With that much in statistics, will have seen a lot of applied probability and may be ready for the real stuff. For that, need measure theory, e.g., the first half of…
…natural language processing, singular value decomposition, AI, ML, principal components analysis, support vector machines, collaborative filtering, cluster analysis, intuitive heuristics, neural nets, classification and regression trees (L. Breiman's CART), random forests, gradient descent, etc. Instead, I just derived some new math; I'm supposed to be able to do that; I've done it before on other practical problems of wide variety.…
…模型的应用在某种合理的意义上（虽然极少被明确说明）会贴近训练数据。这种拟合至少可以追溯到 Leo Breiman、Jerome H. Friedman、Richard A. Olshen、Charles J. Stone 的《Classification and Regression Trees》（ISBN 0-534-98054-6，Wadsworth & Brooks/Cole，加州太平洋丛林，1984年），根本不算什么新东西。这项成果通常被称为 CART，而且早就有了相应的软件。而且 CART 还能追溯到…
…Applications of the model will in some suitable sense, rarely made clear, be close to the training data. Such fitting goes back at least to Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone, Classification and Regression Trees, ISBN 0-534-98054-6, Wadsworth & Brooks/Cole, Pacific Grove, California, 1984. not nearly new. This work is commonly called CART, and there has long been corresponding software. And CART goes back…
…用 TeX 标记表示：N.\ R.\ Draper and H.\ Smith, {\it Applied Regression Analysis,\/} John Wiley and Sons, New York, 1968.\ \ Leo Breiman, Jerome H.\ Friedman, Richard A.\ Olshen, Charles J.\ Stone, {\it Classification and Regression Trees,\/} ISBN 0-534-98054-6, Wadsworth \& Brooks/Cole, Pacific Grove, California, 1984.\ \ C.\ Radhakrishna Rao, {\it Linear Statistical Inference and Its Applications:\ \ Second Edition,\/} ISBN 0-471-70823-2, John…
…with TeX markup: N.\ R.\ Draper and H.\ Smith, {\it Applied Regression Analysis,\/} John Wiley and Sons, New York, 1968.\ \ Leo Breiman, Jerome H.\ Friedman, Richard A.\ Olshen, Charles J.\ Stone, {\it Classification and Regression Trees,\/} ISBN 0-534-98054-6, Wadsworth \& Brooks/Cole, Pacific Grove, California, 1984.\ \ C.\ Radhakrishna Rao, {\it Linear Statistical Inference and Its Applications:\ \ Second Edition,\/} ISBN 0-471-70823-2, John…
…SVM（支持向量机）本质上是一种曲线拟合的应用，跟经典多元统计里的判别分析（discriminate analysis）有关。它与树模型的联系，大概很像 Breiman 等人的《Classification and Regression Trees》（CART）里的那种，那是应用统计学的一部经典著作。Breiman 曾是一位出色的数学家、概率学家兼应用统计学家。Machine Learning 跟人类学习或心理学意义上的学习完全是两码事。这门课看起来…
…(support vector machines) is an application of curve fitting related to discriminate analysis in classic multi-variate statistics. The connections with trees are likely much as in the Breiman, et al., Classification and Regression Trees (CART), a classic in applied statistics. Breiman was a good mathematician, probabilist, and applied statistician. Machine Learning is nothing like learning in humans or psychology. The course looks…
…普通回归要是效果不灵，那我就不太愿意硬去折腾更复杂的玩意儿了。在某些情况下，我可能还愿意试试 L. Breiman（我很尊敬 Breiman，他是 Loeve 的学生）在他的《Classification and Regression Trees》里写的那套东西。
…ordinary regression doesn't work very well, then I'm reluctant to strain with much more. I might be willing in some circumstances to use what L. Breiman (I respect Breiman, Loeve student) has in his Classification and Regression Trees.
…尤其是，掌握的程度要足以理解回归就是正交投影（perpendicular projection），从而再次把勾股定理给串起来。要想进一步了解面向机器学习的这类统计学，去搞一本 Breiman 的 CART——《Classification and Regression Trees》，这大概算得上 ML 的很大一部分源头。学了这么多统计学，你见过的应用概率论就相当多了，可能可以去啃真家伙了。为此，你需要懂测度论，比如前半部分的…
…particular, get enough to understand that regression is a perpendicular projection and, thus, get the Pythagorean theorem again. For more on such statistics aimed at machine learning, get the Breiman CART -- Classification and Regression Trees, maybe much of the start of ML. With that much in statistics, will have seen a lot of applied probability and may be ready for the real stuff. For that, need measure theory, e.g., the first half of…
…自然语言处理、奇异值分解、AI、ML、主成分分析、支持向量机、协同过滤、聚类分析、直觉启发式、神经网络、分类与回归树（L. Breiman 的 CART）、随机森林、梯度下降等。相反，我只是推导了一些新的数学方法；按理说我本来就该有这本事；以前在各种各样的实际问题上我也这么干过。…
…natural language processing, singular value decomposition, AI, ML, principal components analysis, support vector machines, collaborative filtering, cluster analysis, intuitive heuristics, neural nets, classification and regression trees (L. Breiman's CART), random forests, gradient descent, etc. Instead, I just derived some new math; I'm supposed to be able to do that; I've done it before on other practical problems of wide variety.…
…模型的应用在某种合理的意义上（虽然极少被明确说明）会贴近训练数据。这种拟合至少可以追溯到 Leo Breiman、Jerome H. Friedman、Richard A. Olshen、Charles J. Stone 的《Classification and Regression Trees》（ISBN 0-534-98054-6，Wadsworth & Brooks/Cole，加州太平洋丛林，1984年），根本不算什么新东西。这项成果通常被称为 CART，而且早就有了相应的软件。而且 CART 还能追溯到…
…Applications of the model will in some suitable sense, rarely made clear, be close to the training data. Such fitting goes back at least to Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone, Classification and Regression Trees, ISBN 0-534-98054-6, Wadsworth & Brooks/Cole, Pacific Grove, California, 1984. not nearly new. This work is commonly called CART, and there has long been corresponding software. And CART goes back…