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') ...
1. 简介 树模型直白且清晰,它即可以用来分类也可以用来预测,他最大的特点是容易解释,这在实际应用中十分关键。树通过在predictor中创建许多的分支来创建(IF ELSE)的规则,例如"IF 年龄<55 and 学历>2,则分类为1"。树的创建的基本思想包括两条,第一,recursive partitioning (用于树的构建),第二,pruning(用于树...
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...
But perhaps the most common, and most important machine learning tasks – especially for beginners – are regression and classification. Let’s look at regression and classification and see how they compare to eachother as machine learning tasks. After we do that, we’ll look at how they’re ...
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...
LASSO回归（Least Absolute Shrinkage and Selection Operator）是一种正则化线性回归方法，它通过在损失函数...
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:...
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...
随机森林模型在分类与回归分析中的应用 Using Random Forest for classification and regression Random forest is an algorithm developed by Breiman and Cutler in 2001. It runs by constructing multiple decision trees while training and outputting the cl... Xinhai Li - 《Journal of Applied Entomology》 ...
Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples of the training data and random feature selection in tree induction. Prediction is made by aggregating (majority vote or averaging) the predictions of the ensemble. We built predictive ...