与机器学习相比，Statistical learning是基于具有少数属性的较小的数据集，而Machine learning可以从数十亿（...
machine learning是计算机科学和人工智能的一个子领域,用于构建可以从数据中学习到model,而不需要显示地编程学习rule statistical model:是数学的一个分支,用于发现多个变量之间的关系,从而可以预测输出 diffrent eras(不同时代的产物) statistical modelling已经存在几世纪的时间了,而machine learning实际上从1990年代才变得...
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...
Machine Learning: online learning, semisupervised learning, manifold learning, active learning, boosting. But the differences become blurrier all the time. Check out two flagship journals: The Annals of StatisticsandThe Journal of Machine Learning Research. The overlap in topics is striking. And many...
When we are using machine learning models, we typically don’t make any substantial/particular assumptions like non-collinearity, normally distributed residuals, etc. The absolute predictive performance of ML models is usually better than for statistical models (although, they often don’t have the ...
上一讲讲完了有关什么是machine learning以及machine learning的分类后,这一讲就先从statistical machine learning 开始讲。 首先说说statistical machine learning的framework。 Input:n个具有iid(独立同分布…
This articles tries to list the differences between the statistics fields. The best one would be to consider Machine Learning and Data Mining as applied statistics. Leo Breiman, Statistical Modeling: The Two Cultures, Statistical Science 16(3), 2
Data Mining, Machine Learning Vs Data science Statistical Analysis Some Examples of Machine Learning Conclusion What is Data Mining? Data mining which is also known as Knowledge Discovery Process is a field of science that is used to find out the properties of datasets. Large sets of data collec...
Machine Learning Algorithms Algorithms are the computational part of a machine learning project. Once trained, algorithms produce models with a statistical probability of answering a question or achieving a goal. That goal might be finding certain features in images, such as “identify all the cats,...
I’ve been hearing lots of friends compare two dueling courses at Stanford: CS229, the CS department’s “machine learning” course taught by Andrew Ng; and Stat 315 A/B, the Statistics department’s “statistical learning” sequence taught by some combination of Tibshirani, Jerome Friedman, ...