Our task is to predict the category of this data sample. At this time, there is an unmarked data sample. Specifically, suppose we have a labeled data set. The core idea of knn algorithm is the category of unlabeled samples, which is decided by the nearest k neighbors. In short, let the machine itself according to the distance of each point, and the close ones are classified as one kind. The first letter k can be lowercase, indicating the number of externally defined nearest neighbors. Its idea is very simple: if most of the samples of multiple nearest neighbors (most similar) in the feature space belong to a category, the sample also belongs to this category. It uses the method of measuring the distance between different eigenvalues for classification. K-nearest neighbor algorithm is a relatively simple machine learning algorithm.
#Nearest neighbor matlab 2012 code
GPU Arrays Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.2.1 advantages and disadvantages of the algorithmĤ.5 # sorting and outputting test results Returns double-precision indices to match the MATLAB behavior.įor more information on code generation, see Introduction to Code Generation and General Code Generation Workflow. For MEX code generation, the function still Support when you use single-precision inputs. Therefore, the function allows for strict single-precision Integer-type ( int32) indices, rather than double-precision indices, in To disable OpenMP library, set the EnableOpenMP property of theĭetails, see coder.CodeConfig (MATLAB Coder). To find supported compilers, see Supported Compilers. If your compilerĭoes not support the Open Multiprocessing (OpenMP) application interface or you disable OpenMPĬoder™ treats the parfor-loops as for-loops. Parallel on supported shared-memory multicore platforms in the generated code. Knnsearch uses parfor (MATLAB Coder) to create loops that run in MEX function for the exhaustive search algorithm and standalone C/C++ code for both For details, see coder.MexCodeConfig (MATLAB Coder). Set the ExtrinsicCalls property of the MEXĬonfiguration object to false. Parfor version, you can disable the usage of Intel TBB. If you generate the MEX function to test the generated code of the You can use the MEXįunction to accelerate MATLAB algorithms. MEX function for the kd-tree search algorithm -Ĭodegen generates an optimized MEX function using Intel TBB for parallel computation on multicore platforms. Otherwise,Ĭodegen generates code using parfor (MATLAB Coder). Intel ® Threading Building Blocks (TBB) for parallel computation. Kd-tree search algorithm, and the code generation build type is a MEXįunction, codegen (MATLAB Coder) generates a MEX function using 'IncludeTies' as true, the sorted order of tiedĭistances in the generated code can be different from the order in MATLAB ® due to numerical precision. The -args value of codegen (MATLAB Coder). For example, to allow a user-defined exponent for the Minkowski distance in the
Names in name-value pair arguments must be compile-time constants. The 'SortIndices' name-value pair argument is not The value of the 'IncludeTies' name-value pairĪrgument must be a compile-time constant.
The value of the 'Distance' name-value pair argument must be a compile-time constant and cannot be a custom distance function. 'exhaustive' when the number of columns in X is The default value of the 'NSMethod' name-value pair argument is You can also specify a function handle for a customĭistance metric by using (for A custom distance function must: One minus the Jaccard coefficient, which is the Hamming distance, which is the percentage of One minus the sample Spearman's rank correlationīetween observations (treated as sequences of One minus the sample linear correlation between One minus the cosine of the included angleīetween observations (treated as vectors). Mahalanobis distance, computed using a positiveĭefinite covariance matrix. Scaled by dividing by the corresponding element of
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