关于旋转森林的MATLAB程序 - Matlab在线 - matlabol

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Rotate the forest RotationPforest

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中文说明：

旋转森林最近热门的集成学习分类方法，可用于模式识别分类。

当输入数据中存在非线性关系的时候，基于线性回归的模型就会失效，而基于树的算法则不受数据中非线性关系的影响，基于树的方法最大的一个困扰时为了避免过拟合而对树进行剪枝的难度，对于潜在数据中的噪声，大型的树倾向于受影响，导致低偏差（过度拟合）或高方差（极度不拟合）。不过如果我们生成大量的树，最终的预测值采用集成所有树产生的输出的平均值，就可以避免方差的问题。

English Description：

The recently popular ensemble learning classification method of rotation forest can be used for pattern recognition and classification. When there is a nonlinear relationship in the input data, the model based on linear regression will be invalid, while the tree based algorithm is not affected by the nonlinear relationship in the data. The biggest problem of the tree based method is to avoid the difficulty of pruning the tree in order to avoid over fitting. For the noise in the potential data, large trees tend to be affected, resulting in low deviation (over fitting) Or high square deviation (extremely non fitting). However, if we generate a large number of trees and the final predicted value is the average value of the output generated by integrating all the trees, we can avoid the problem of variance.

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Rotation forest-5.25实验室

..........................\Accury.m

..........................\AdaBoost.m

..........................\bagging.asv

..........................\bagging.m

..........................\bagging1.asv

..........................\bagging1.m

..........................\cross_val.asv

..........................\cross_val.m

..........................\fea_crossval.asv

..........................\fea_crossval.m

..........................\majorityvote.m

..........................\nearestneighbour.m

..........................\newRM_demo.asv

..........................\newRM_demo.m

..........................\new_crossval.m

..........................\new_Rotation.m

..........................\new_Rotation_Matrix.m

..........................\new_RotForest.asv

..........................\new_RotForest.m

..........................\PCA.m

..........................\RandomSelect.m

..........................\RM_demo.asv

..........................\RM_demo.m

..........................\RM_PCA.asv

..........................\RM_PCA.m

..........................\Rotation.m

..........................\Rotation_Matrix.asv

..........................\Rotation_Matrix.m

..........................\RotForest.asv

..........................\RotForest.m

..........................\RotForest_PCA.asv

..........................\RotForest_PCA.m

..........................\RSM.m

..........................\RSM_PCA.m

..........................\test.m

..........................\test_1.m

..........................\test_2.m

..........................\test_3.m

..........................\test_test.m

..........................\Train_Test.m

..........................\uci_data

..........................\........\aba.mat

..........................\........\abalone.names

..........................\........\bala.mat

..........................\........\balance-scale.names

..........................\........\bcw.mat

..........................\........\breast-cancer-wisconsin.names

..........................\........\car.mat

..........................\........\car.names

..........................\........\cmc.mat

..........................\........\cmc.names

..........................\........\derm.mat

..........................\........\dermatology.names

..........................\........\ecoli.mat

..........................\........\ecoli.names

..........................\........\feret.mat

..........................\........\FERET_32x32.mat

..........................\........\haberman.mat

..........................\........\haberman.names

..........................\........\housing.mat

..........................\........\housing.names

..........................\........\movement.mat

..........................\........\movement_libras.names

..........................\........\pima-indians-diabetes.names

..........................\........\pima.mat

..........................\........\soybean-small.names

..........................\........\soybean.mat

..........................\........\wine.mat

..........................\........\wine.names

..........................\........\yeast.mat

..........................\........\yeast.names

..........................\........\zoo.mat

..........................\........\zoo.names

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