孤立森林matlab代码
时间: 2023-11-25 13:57:00 浏览: 60
孤立森林(Isolation Forest)是一种快速检测异常点的算法,它利用了树结构的分割能力来快速定位异常点。以下是使用Matlab实现孤立森林的示例代码:
```
function [scores, trees] = isolationForest(X, numTrees, sampleSize)
% X: 数据集,每行是一个样本
% numTrees: 森林中树的数量
% sampleSize: 每个树使用的样本数量
[n, d] = size(X);
trees = cell(numTrees, 1);
for i = 1:numTrees
% 随机采样样本
sampleIdx = randsample(n, sampleSize);
Xsample = X(sampleIdx, :);
% 构建孤立树
tree = isolationTree(Xsample);
trees{i} = tree;
end
scores = zeros(n, 1);
for i = 1:n
x = X(i, :);
pathLengths = zeros(numTrees, 1);
for j = 1:numTrees
tree = trees{j};
pathLengths(j) = getPathLength(tree, x, 0);
end
scores(i) = mean(pathLengths);
end
end
function tree = isolationTree(X)
% 构建孤立树
[n, d] = size(X);
if n <= 1
tree = struct('left', [], 'right', [], 'splitAtt', [], 'splitValue', [], 'size', n);
return;
end
% 随机选择一个属性
splitAtt = randi(d);
% 随机选择一个分割点
minVal = min(X(:, splitAtt));
maxVal = max(X(:, splitAtt));
splitValue = unifrnd(minVal, maxVal);
% 分割数据
leftIdx = X(:, splitAtt) < splitValue;
rightIdx = ~leftIdx;
leftX = X(leftIdx, :);
rightX = X(rightIdx, :);
% 构建孤立树
leftTree = isolationTree(leftX);
rightTree = isolationTree(rightX);
tree = struct('left', leftTree, 'right', rightTree, 'splitAtt', splitAtt, 'splitValue', splitValue, 'size', n);
end
function pathLength = getPathLength(tree, x, pathLength)
% 获取样本x在孤立树tree上的路径长度
if isempty(tree.left) && isempty(tree.right)
pathLength = pathLength + 1;
return;
end
splitAtt = tree.splitAtt;
splitValue = tree.splitValue;
if x(splitAtt) < splitValue
pathLength = getPathLength(tree.left, x, pathLength + 1);
else
pathLength = getPathLength(tree.right, x, pathLength + 1);
end
end
```
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