统计学习基础

• 吾往

  2017-02-27
  This example also shows that neural networks are not a fully automatic tool, as they are sometimes advertised. As with all statistical models, subject matter knowledge can and should be used to improve their performance.
• 吾往

  2017-02-27
  The clever design of network Net-5, motivated by the fact that features of handwriting style should appear in more than one part of a digit, was the result of many person years of experimentation.
• Ms.蔬菜

  2015-02-05
  Although the individual class density estimates may be biased, this bias might not hurt the posterior probabilities as much, esp near the decision regions. In fact the problem may be able to withstand considerable bias for the savings in variances such as naive assumption earns.
• 豆友1907570

  2013-07-25
  在R. A. Fisher提出的著名的艾里斯(Iris)判别例子中……
• [已注销]

  2013-07-08
  I take it that the question is about LDA and linear (not logistic) regression.There is a considerable and meaningful relation between linear regression and linear discriminant analysis. In case the DV consisting just of 2 groups the two analyses are actually identical. Despite that computations are different and the results - regression and discriminant coefficients - are not the same, they are exactly proportional to each other.Now for the more-than-two-groups situation. First, let us state that LDA (its extraction, not classification stage) is equivalent (linearly related results) to canonical correlation analysis if you turn the grouping DV into a set of dummy variables (with one redundant of them droped out) and do canonical analysis with sets "IVs" and "dummies". Canonical variate...
• pennlio

  2013-05-06
  On interpretation
• 大刀

  2011-11-28
  "over-all five or ten fold cross-validation are recommended as a good compromise"
• 大刀

  2011-11-28
  “In-sample error is not usually of direct interest since future values of the features are not likely to coincide with their training set value.But for comparison between models,in-sample error is convenient and often leads to effective model selection”
• 大刀

  2011-11-03
  A retrospective sample of males in a heart-disease high-risk regionof the Western Cape, South Africa. There are roughly two controls percase of CHD. Many of the CHD positive men have undergone bloodpressure reduction treatment and other programs to reduce their riskfactors after their CHD event. In some cases the measurements weremade after these treatments. These data are taken from a largerdataset, described in Rousseauw et al, 1983, South African MedicalJournal. sbpsystolic blood pressuretobaccocumulative tobacco (kg)ldllow densiity lipoprotein cholesteroladiposityfamhistfamily history of heart disease (Present, Absent)typeatype-A behaviorobesityalcoholcurrent alcohol consumptionageage at onsetchdresponse, coronary heart disease
• 36°

  2011-09-06
  To get an ida of why, note that if the neighborhoods were nonoverlapping, there would be N/k neighborhoods and we would fit one parameter (a mean) in each neighborhood.
• 换个ID试试

  2016-07-26
  Scenario 1: The training data in each class were generated from bivariate Gaussian distributions with uncorrelated components and different means.- Scenario 2: The training data in each class came from a mixture of 10 low-variance Gaussian distributions, with individual means themselves distributed as Gaussian.
• 孔明

  2013-04-11
  The clever design of network Net-5, motivated by the fact that features of handwriting style should appear in more than one part of a digit, was the result of many years of experimentation.
• 孔明

  2012-11-09
  However, with a 0 − 1 outcome, this computation simplifies. We order the predictor classes according to the proportion falling in outcome class 1. Then we split this predictor as if it were an ordered predictor.
• t君

  2012-07-13
  Both k-nearest neighbors and least squares end up approximating conditional expectatios by averages.
• Aron

  2015-01-27
  还是觉得对这本书相见恨晚，研一写那么都web app有毛用啊，就应该踏踏实实的多读书啊~ 还好去实习了，还好发现原来啥都不知道，还好坚持把这本书啃完了，虽然理解的较为粗陋，要不要去读个博呢......真苦恼~
• Aron

  2015-01-25
  Bagging; or Bootstrap AGGregatING, is an extension of bootstrapping to classification and regression problems. The main idea is to sample with replacement from the training data so that we now have B training data sets, each having n′≤n observations. The machine-learning algorithm is trained on each of the B data sets to form a committee.
• Aron

  2015-01-25
  有一个关于Metropolis算法的故事，非常流行：一晚，Edward、Metropolis和Marshall在派对上讨论这个问题，在鸡尾酒餐巾纸上写出了这个闻名的算法。他们最终的论文之所以写上妻子的名字，是为了安抚被整晚的技术性讨论所烦扰的女人Arianna和Augusta
• Aron

  2015-01-25
  Monte Carlo is an extremely bad method; it should be used onlywhen all alternative methods are worse
• 孔明

  2013-04-11
  the bias of the 1-nearest-neighbor estimate is often low, but the variance is high.
• 维法钵扎店

  2013-08-03
  LAR uses least squares directions in the active set of variables.Lasso uses least square directions; if a variable crosses zero, it is removed from the active set.Boosting uses non-negative least squares directions in the active set.