Skip to main content
Ctrl+K
oneDAL documentation - Home

About

  • 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

Kernel Functions

Kernel Functions#

This chapter describes programming interfaces of the kernel functions implemented in oneDAL:

  • Linear kernel
  • Polynomial kernel
  • Radial Basis Function (RBF) kernel
  • Sigmoid kernel

previous

Connected Components

next

Linear kernel

© Copyright Intel Corporation.

Cookies | Privacy | Do Not Share My Personal Information
© Intel Corporation. Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others. No license (express or implied, by estoppel or otherwise) to any intellectual property rights is granted by this document, with the sole exception that code included in this document is licensed subject to the Zero-Clause BSD open source license (OBSD), http://opensource.org/licenses/0BSD.

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