Classification and Regression Training Miscellaneous functions for training and plotting classification and regression models. Detailed documentation is athttp://topepo.github.io/caret/index.html Install the current release from CRAN: install.packages('caret') ...
If one or more of our predictors can be predicted from other predictors, it can produce a state ofmulticollinearityin our model. Multicollinearity is a challenge because it can skew the results of regression models (both linear and logistic) and reduce the predictive or classifying p...
Let’s say that you want make a model that predicts whether a person will buy a particular product. The possible output categories would be “buy” and “no buy”. But if we recode “buy” as 1 and “no buy” as 0, we can apply logistic regression. So by re-coding the target var...
caret: Classification and Regression Training. https://CRAN.R-project.org/package=caret (2019). Accessed 10 Dec 2019. Raschka S Model evaluation, model selection, and algorithm selection in machine learning. arXiv:181112808 [cs, stat]. http://arxiv.org/abs/1811.12808 (2018). Accessed 10 ...
classification,averageforregression). Anestimateoftheerrorratecanbeobtained, basedonthetrainingdata,bythefollowing: 1.Ateachbootstrapiteration,predictthedata notinthebootstrapsample(whatBreiman calls“out-of-bag”,orOOB,data)usingthetree grownwiththebootstrapsample. 2.AggregatetheOOBpredictions.(Onthe...
the sampling proportion for each class with respect to the lowest-represented class. For example, suppose that there are two classes in the training data:AandB.Ahave 100 observations andBhave 10 observations. Also, suppose that the lowest-represented class hasmobservations in the training data. ...
Classification: This is just like the regression problem, except that the values y we now want to predict take on only a small number of discrete values. For now, we will focus on the binary classification problem in which y can take on only two values, 0 and 1. 0 is also called the...
When y is numerical we apply kNN regression. Divide the dataset into two, with m data-points consisting of the test set and the remaining n−m data-points the training set. To do this randomly permute the n data-points, take the first m data-points as the test set and the remaining...
分类问题的training data 那这里有一个问题,那就是我们知道监督学习还有一种问题就是Regression,他的输出是一个scalar值。我们可不可以考虑使用regression来解决classification问题呢?比如对于二分类的问题为例来说,使用regression来解决,因为regression输出是一个scalar,所以我们可以把输出接近1的看成是class 1,而输出接近...
average for regression). sifiers and aggregate their results. Two well-known methods are boosting (see, e.g., Shapire et al., 1998) An estimate of the error rate can be obtained, and bagging Breiman (1996) of classification trees. In based on the training data, by the following:...