matlab查找最臨近搜索knnsearch

Idx = knnsearch(X,Y) finds the nearest neighbor in X for each query point in Y and returns the indices of the nearest neighbors in Idx, a column vector. Idx has the same number of rows as Y.

為Y中的每個查詢點在X中查找最近的鄰居，並返回IDX(列向量)中最近鄰居的索引。IDX的行數與y相同。

Idx = knnsearch(X,Y,Name,Value) returns Idx with additional options specified using one or more name-value pair arguments. For example, you can specify the number of nearest neighbors to search for and the distance metric used in the search.

返回IDX，並使用一個或多個名稱-值對參數指定其他選項。例如，可以指定要搜索的最近鄰居的數目和搜索中使用的距離度量。

[Idx,D] = knnsearch(___) additionally returns the matrix D, using any of the input arguments in the previous syntaxes. D contains the distances between each observation in Y and the corresponding closest observations in X.

使用先前語法中的任何輸入參數返回矩陣D。D包含Y中每個觀測值與X中對應的最近觀測值之間的距離。

舉例：

Load Fisher's iris data set.

load fisheriris
X = meas(:,3:4); % Measurements of original flowers
Y = [5 1.45;6 2;2.75 .75]; % New flower data

Perform a knnsearch between X and the query points Y using Minkowski and Chebychev distance metrics.

使用Minkowski和chebychev距離度量在x和查詢點y之間執行 knnsearch。

[mIdx,mD] = knnsearch(X,Y,'K',10,'Distance','minkowski','P',5);
[cIdx,cD] = knnsearch(X,Y,'K',10,'Distance','chebychev');

Visualize the results of the two nearest neighbor searches. Plot the training data. Plot the query points with the marker X. Use circles to denote the Minkowski nearest neighbors. Use pentagrams to denote the Chebychev nearest neighbors.

可視化兩個最近鄰搜索的結果。繪制訓練數據。用標記x繪制查詢點。用圓表示Minkowski最近的鄰居。用五角星表示切比雪夫最近的鄰居。

gscatter(X(:,1),X(:,2),species);
line(Y(:,1),Y(:,2),'Marker','x','Color','k',...
'Markersize',10,'Linewidth',2,'Linestyle','none');
line(X(mIdx,1),X(mIdx,2),'Color',[.5 .5 .5],'Marker','o',...
'Linestyle','none','Markersize',10);
line(X(cIdx,1),X(cIdx,2),'Color',[.5 .5 .5],'Marker','p',...
'Linestyle','none','Markersize',10);
legend('setosa','versicolor','virginica','query point',...
'minkowski','chebychev','Location','best');

來源：https://ww2.mathworks.cn/help/stats/knnsearch.html?searchHighlight=knnsearch&s_tid=doc_srchtitle