11)统计学习基础(Elements of Statistical Learning): 书《The Elements of Statistical Learning: Data Mining, Inference, and Prediction 》(http://www-stat.stanford.edu/~tibs/ElemStatLearn/)里的数据集、函数、例子都被打包放在ElemStatLearn包里(http://cran.r-project.org/web/packages/ElemStatLearn/inde...
Statistical learning refers to a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning. The field encompasses many methods such as the lasso and sparse...
Daniela Witten is an associate professor of statistics and biostatistics at the University of Washington. Her research focuses largely on statistical machine learning in the high-dimensional setting, with an emphasis on unsupervised learning. Trevor Hastie and Robert Tibshirani are professors of statistics...
— As the covid-19 pandemic stroke the humanity on March 2020, the Higher Education Institutions had to confront rapidly the emergency to readapt the organization of their courses in order to respond to those extenuating circumstances. An Emergency Remote Teaching Environment (ERTE) [1][10] was...
We describe methods for learning probability models—primarily Bayesian networks— in Sections 20.2 and 20.3. Section 20.4 looks at learning methods that store and recall specific instances. Section 20.5 covers neural network learning and Section 20.6 introduces kernel machines. Some of the material i...
The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This ...
In recent years, machine learning and statistical modeling techniques have attracted extensive attention in image indexing and retrieval. In this chapter, we reviewed five machine learning and statistical modeling techniques to be used in the remaining o
Smile (Statistical Machine Intelligence and Learning Engine) is a set of pure Java libraries of various state-of-art machine learning algorithms. Smile is self contained and requires only Java standard library. The major components include Core The core machine learning library Math Linear algebra, ...
本文使用 Zhihu On VSCode 创作并发布Masashi Sugiyama 杉山将著,Introduction to Statistical Machine Learning 《统计机器学习》的学习小记(4) 之前我们对一维随机变量的概率分布进行了讨论,也做了一些公式的…
Smile (Statistical Machine Intelligence and Learning Engine) is a fast and comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. With advanced data structures and algorithms, Smile delivers state-of-art performance. Smile covers every asp...