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  • Introduction
  • System Requirements

Get Started

  • Installation
  • Quick Start
  • oneAPI Examples
    • DPC++
      • basic_statistics_dense_batch.cpp
      • basic_statistics_dense_online.cpp
      • column_accessor_homogen.cpp
      • cor_dense_batch.cpp
      • cor_dense_online.cpp
      • cov_dense_batch.cpp
      • cov_dense_biased_batch.cpp
      • cov_dense_biased_online.cpp
      • cov_dense_online.cpp
      • csr_accessor.cpp
      • csr_table.cpp
      • dbscan_brute_force_batch.cpp
      • df_cls_hist_batch.cpp
      • df_cls_hist_batch_random.cpp
      • df_cls_traverse_model.cpp
      • df_reg_hist_batch.cpp
      • df_reg_hist_batch_random.cpp
      • df_reg_traverse_model.cpp
      • heterogen_table.cpp
      • homogen_table.cpp
      • kmeans_init_dense.cpp
      • kmeans_lloyd_dense_batch.cpp
      • knn_cls_brute_force_dense_batch.cpp
      • knn_reg_brute_force_dense_batch.cpp
      • knn_search_brute_force_dense_batch.cpp
      • linear_kernel_dense_batch.cpp
      • linear_regression_dense_batch.cpp
      • linear_regression_dense_online.cpp
      • logistic_regression_dense_batch.cpp
      • pca_cor_dense_batch.cpp
      • pca_cor_dense_online.cpp
      • pca_cov_dense_batch.cpp
      • pca_cov_dense_online.cpp
      • pca_precomputed_cor_dense_batch.cpp
      • pca_precomputed_cov_dense_batch.cpp
      • pca_svd_dense_batch.cpp
      • rbf_kernel_dense_batch.cpp
      • read_batch.cpp
      • svm_two_class_thunder_dense_batch.cpp
    • C++
      • basic_statistics_dense_batch.cpp
      • basic_statistics_dense_online.cpp
      • column_accessor_homogen.cpp
      • connected_components_batch.cpp
      • cor_dense_batch.cpp
      • cor_dense_online.cpp
      • cov_dense_batch.cpp
      • cov_dense_biased_batch.cpp
      • cov_dense_biased_online.cpp
      • cov_dense_online.cpp
      • csr_accessor.cpp
      • csr_table.cpp
      • dbscan_brute_force_batch.cpp
      • df_cls_dense_batch.cpp
      • df_reg_dense_batch.cpp
      • directed_graph.cpp
      • graph_service_functions.cpp
      • heterogen_table.cpp
      • homogen_table.cpp
      • jaccard_batch.cpp
      • jaccard_batch_app.cpp
      • kmeans_init_dense.cpp
      • kmeans_lloyd_dense_batch.cpp
      • knn_cls_brute_force_dense_batch.cpp
      • knn_cls_kd_tree_dense_batch.cpp
      • knn_search_brute_force_dense_batch.cpp
      • linear_kernel_dense_batch.cpp
      • linear_regression_dense_batch.cpp
      • linear_regression_dense_online.cpp
      • logloss_dense_batch.cpp
      • louvain_batch.cpp
      • pca_cor_dense_batch.cpp
      • pca_cor_dense_online.cpp
      • pca_cov_dense_batch.cpp
      • pca_cov_dense_online.cpp
      • pca_precomputed_dense_batch.cpp
      • pca_svd_dense_batch.cpp
      • pca_svd_dense_online.cpp
      • polynomial_kernel_dense_batch.cpp
      • rbf_kernel_dense_batch.cpp
      • read_batch.cpp
      • shortest_paths_batch.cpp
      • sigmoid_kernel_dense_batch.cpp
      • subgraph_isomorphism_batch.cpp
      • svm_multi_class_thunder_csr_batch.cpp
      • svm_multi_class_thunder_dense_batch.cpp
      • svm_nu_cls_thunder_csr_batch.cpp
      • svm_nu_cls_thunder_dense_batch.cpp
      • svm_nu_reg_thunder_csr_batch.cpp
      • svm_nu_reg_thunder_dense_batch.cpp
      • svm_reg_thunder_csr_batch.cpp
      • svm_reg_thunder_dense_batch.cpp
      • svm_two_class_smo_csr_batch.cpp
      • svm_two_class_smo_dense_batch.cpp
      • svm_two_class_thunder_csr_batch.cpp
      • svm_two_class_thunder_dense_batch.cpp
      • triangle_counting_batch.cpp

Developer Guide

  • oneAPI Interfaces
    • Introduction
    • Computational Modes
    • Data Management
      • Array
      • Accessors
        • Column accessor
        • Row accessor
      • Data Sources
        • CSV data source
      • Graphs
        • Undirected adjacency vector graph
        • Directed adjacency vector graph
      • Tables
        • Homogeneous table
        • Compressed Sparse Rows (CSR) Table
      • Backend Primitives
    • Algorithms
      • Clustering
        • DBSCAN
        • K-Means
        • K-Means initialization
      • Covariance
        • Covariance
      • Decomposition
        • Principal Components Analysis (PCA)
      • Ensembles
        • Decision Forest Classification and Regression (DF)
      • Graph
        • Subgraph Isomorphism
        • Connected Components
      • Kernel Functions
        • Linear kernel
        • Polynomial kernel
        • Radial Basis Function (RBF) kernel
        • Sigmoid kernel
      • Logistic Regression
      • Linear Regression
        • Linear Regression
      • Nearest Neighbors (kNN)
        • k-Nearest Neighbors Classification, Regression, and Search (k-NN)
      • Objective function
        • Logistic Loss
      • Optimizers
      • Pairwise Distances
        • Minkowski distance
        • Chebyshev distance
        • Cosine distance
      • Statistics
        • Basic Statistics
      • Support Vector Machines
        • Support Vector Machine Classifier and Regression (SVM)
    • Single Program Multiple Data
    • Appendix
      • Decision Tree
      • k-d Tree
  • DAAL Interfaces
    • CPU and GPU Support
    • Library Usage
      • Algorithms
      • Computation Modes
      • Training and Prediction
        • Classification Usage Model
        • Regression Usage Model
        • Recommendation Systems Usage Model
    • Data Management
      • Numeric Tables
        • Generic Interfaces
        • Essential Interfaces for Algorithms
        • Types of Numeric Tables
      • Data Sources
      • Data Dictionaries
      • Data Serialization and Deserialization
      • Data Model
    • Analysis
      • K-Means Clustering
        • Batch Processing
        • Distributed Processing
        • Batch Processing
        • Distributed Processing
      • Density-Based Spatial Clustering of Applications with Noise
        • Batch Processing
        • Distributed Processing
      • Correlation and Variance-Covariance Matrices
        • Batch Processing
        • Online Processing
        • Distributed Processing
      • Principal Component Analysis
        • Batch Processing
        • Online Processing
        • Distributed Processing
      • Principal Components Analysis Transform
      • Singular Value Decomposition
        • Batch and Online Processing
        • Distributed Processing
      • Association Rules
      • Kernel Functions
      • Expectation-Maximization
      • Cholesky Decomposition
      • QR Decomposition
        • QR Decomposition without Pivoting
        • Pivoted QR Decomposition
      • Outlier Detection
        • Multivariate Outlier Detection
        • Multivariate BACON Outlier Detection
        • Univariate Outlier Detection
      • Distance Matrix
        • Correlation Distance Matrix
        • Cosine Distance Matrix
      • Distributions
        • Uniform Distribution
        • Normal Distribution
        • Bernoulli Distribution
      • Engines
        • mcg59
        • mt19937
        • mt2203
        • mrg32k3a
        • philox4x32x10
      • Moments of Low Order
        • Batch Processing
        • Online Processing
        • Distributed Processing
      • Quantile
      • Quality Metrics
        • Working with the Default Metric Set
        • Working with User-defined Quality Metrics
      • Sorting
      • Normalization
        • Z-score
        • Min-max
      • Optimization Solvers
        • Objective Function
        • Iterative Solver
    • Training and Prediction
      • Decision Forest
        • Decision Forest
        • Regression Decision Forest
        • Classification Decision Forest
      • Decision Trees
        • Decision Tree
        • Regression Decision Tree
        • Classification Decision Tree
      • Gradient Boosted Trees
        • Gradient Boosted Trees
        • Regression Gradient Boosted Trees
        • Classification Gradient Boosted Trees
      • Stump
        • Classification Stump
        • Regression Stump
      • Linear and Ridge Regressions
        • Linear Regression
        • Ridge Regression
        • Linear and Ridge Regressions Computation
      • LASSO and Elastic Net Regressions
        • LASSO
        • Elastic Net
        • LASSO and Elastic Net Computation
      • k-Nearest Neighbors (kNN) Classifier
      • Implicit Alternating Least Squares
        • Batch Processing
        • Distributed Processing
        • Batch Processing
        • Distributed Processing: Training
        • Distributed Processing: Prediction of Ratings
      • Logistic Regression
      • Naïve Bayes Classifier
        • Batch Processing
        • Online Processing
        • Distributed Processing
      • Support Vector Machine Classifier
      • Multi-class Classifier
      • Boosting
        • AdaBoost Classifier
        • AdaBoost Multiclass Classifier
        • BrownBoost Classifier
        • LogitBoost Classifier
    • Services
      • Extracting Version Information
      • Handling Errors
      • Managing Memory
      • Managing the Computational Environment
      • Providing a Callback for the Host Application
  • Bibliography
  • Deprecation Notice

Developer Reference

  • C++ API
    • Data Management
      • Array
      • Accessors
        • Column Accessor
        • Compressed Sparse Rows (CSR) Accessor
        • Row Accessor
      • Data Sources
        • CSV data source
      • Graphs
        • Undirected adjacency vector graph
        • Directed adjacency vector graph
      • Graph Service
        • Undirected adjacency vector graph service
        • Directed adjacency vector graph service
      • Tables
        • Homogeneous table
        • Compressed Sparse Rows (CSR) Table
      • Backend Primitives
        • Multidimensional view
        • Multidimensional array
    • Algorithms
      • Clustering
        • DBSCAN
        • K-Means
        • K-Means initialization
      • Covariance
        • Covariance
      • Decomposition
        • Principal Components Analysis (PCA)
      • Ensembles
        • Decision Forest Classification and Regression (DF)
      • Graph
        • Subgraph Isomorphism
        • Connected Components
      • Kernel Functions
        • Linear kernel
        • Polynomial kernel
        • Radial Basis Function (RBF) kernel
        • Sigmoid kernel
      • Logistic Regression
        • Logistic Regression
      • Linear Regression
        • Linear Regression
      • Nearest Neighbors (kNN)
        • k-Nearest Neighbors Classification (k-NN)
      • Optimizers
        • Newton-CG Optimizer
      • Objective function
        • Objective function
        • Logistic Loss
      • Pairwise Distances
        • Minkowski distance
        • Chebyshev distance
        • Cosine distance
      • Statistics
        • Basic Statistics
      • Support Vector Machines
        • Support Vector Machine Classifier (SVM)
    • Distributed Model: Single Process Multiple Data
      • Distributed SPMD model
      • Communicators

Contributing Guide

  • Coding Guidelines
  • Ideas for contributions

Custom Components

  • CPU Features Dispatching
  • Threading Layer
  • .rst

Nearest Neighbors (kNN)

Nearest Neighbors (kNN)#

  • k-Nearest Neighbors Classification, Regression, and Search (k-NN)

Examples: k-Nearest Neighbors

Batch Processing:

  • knn_cls_brute_force_dense_batch.cpp

Batch Processing:

  • knn_cls_brute_force_dense_batch.cpp

  • knn_cls_kd_tree_dense_batch.cpp

  • knn_search_brute_force_dense_batch.cpp

Distributed Processing:

  • uxlfoundation/scikit-learn-intelex

  • uxlfoundation/scikit-learn-intelex

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Linear Regression

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k-Nearest Neighbors Classification, Regression, and Search (k-NN)

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oneDAL is licensed under Apache License Version 2.0. Refer to the LICENSE file for the full license text and copyright notice.