Intel® oneAPI Data Analytics Library Developer Guide and Reference

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ID 772611
Date 12/16/2022
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Document Table of Contents
Document Table of Contents x
Intel® oneAPI Data Analytics Library (oneDAL)
Intel® oneAPI Data Analytics Library (oneDAL) x
Data Analytics Pipeline Installation System Requirements oneAPI Interfaces DAAL Interfaces Bibliography C++ API Notices and Disclaimers
oneAPI Interfaces x
Introduction Computational Modes Data Management Algorithms Single Program Multiple Data oneAPI Examples Appendix
Introduction x
Build applications with oneDAL Glossary Mathematical Notations
Data Management x
Array Accessors Data Sources Graphs Tables
Accessors x
Column accessor Row accessor
Data Sources x
CSV data source
Graphs x
Undirected adjacency vector graph Directed adjacency vector graph
Tables x
Homogeneous table
Algorithms x
Clustering Covariance Decomposition Ensembles Graph Kernel Functions Nearest Neighbors (kNN) Pairwise Distances Statistics Support Vector Machines
Clustering x
DBSCAN K-Means K-Means initialization
Covariance x
Covariance
Decomposition x
Principal Components Analysis (PCA)
Ensembles x
Decision Forest Classification and Regression (DF)
Graph x
Subgraph Isomorphism Connected Components
Kernel Functions x
Linear kernel Polynomial kernel Radial Basis Function (RBF) kernel Sigmoid kernel
Nearest Neighbors (kNN) x
k-Nearest Neighbors Classification and Search (k-NN)
Pairwise Distances x
Minkowski distance Chebyshev distance Cosine distance
Statistics x
Basic Statistics
Support Vector Machines x
Support Vector Machine Classifier and Regression (SVM)
oneAPI Examples x
DPC++ C++
DPC++ x
basic_statistics_dense_batch.cpp column_accessor_homogen.cpp cor_dense_batch.cpp cov_dense_batch.cpp dbscan_brute_force_batch.cpp df_cls_hist_batch.cpp df_cls_traverse_model.cpp df_reg_hist_batch.cpp df_reg_traverse_model.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 pca_cor_dense_batch.cpp pca_precomputed_cor_dense_batch.cpp pca_precomputed_cov_dense_batch.cpp rbf_kernel_dense_batch.cpp svm_two_class_thunder_dense_batch.cpp
C++ x
basic_statistics_dense_batch.cpp column_accessor_homogen.cpp connected_components_batch.cpp cor_dense_batch.cpp cov_dense_batch.cpp dbscan_brute_force_batch.cpp df_cls_dense_batch.cpp df_reg_dense_batch.cpp directed_graph.cpp graph_service_functions.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 louvain_batch.cpp pca_dense_batch.cpp pca_precomputed_dense_batch.cpp polynomial_kernel_dense_batch.cpp rbf_kernel_dense_batch.cpp shortest_paths_batch.cpp sigmoid_kernel_dense_batch.cpp subgraph_isomorphism_batch.cpp svm_multi_class_thunder_dense_batch.cpp svm_nu_cls_thunder_dense_batch.cpp svm_nu_reg_thunder_dense_batch.cpp svm_reg_thunder_dense_batch.cpp svm_two_class_smo_dense_batch.cpp svm_two_class_thunder_dense_batch.cpp triangle_counting_batch.cpp
Appendix x
Decision Tree k-d Tree
DAAL Interfaces x
CPU and GPU Support Library Usage Data Management Analysis Training and Prediction Services
Library Usage x
Algorithms Computation Modes Training and Prediction
Training and Prediction x
Classification Usage Model Regression Usage Model Recommendation Systems Usage Model
Data Management x
Numeric Tables Data Sources Data Dictionaries Data Serialization and Deserialization Data Compression Data Model
Numeric Tables x
Generic Interfaces Essential Interfaces for Algorithms Types of Numeric Tables
Analysis x
K-Means Clustering Density-Based Spatial Clustering of Applications with Noise Correlation and Variance-Covariance Matrices Principal Component Analysis Principal Components Analysis Transform Singular Value Decomposition Association Rules Kernel Functions Expectation-Maximization Cholesky Decomposition QR Decomposition Outlier Detection Distance Matrix Distributions Engines Moments of Low Order Quantile Quality Metrics Sorting Normalization Optimization Solvers
K-Means Clustering x
Batch Processing Distributed Processing Batch Processing Distributed Processing
Density-Based Spatial Clustering of Applications with Noise x
Batch Processing Distributed Processing
Correlation and Variance-Covariance Matrices x
Batch Processing Online Processing Distributed Processing
Principal Component Analysis x
Batch Processing Online Processing Distributed Processing
Singular Value Decomposition x
Batch and Online Processing Distributed Processing
QR Decomposition x
QR Decomposition without Pivoting Pivoted QR Decomposition
QR Decomposition without Pivoting x
Batch and Online Processing Distributed Processing
Outlier Detection x
Multivariate Outlier Detection Multivariate BACON Outlier Detection Univariate Outlier Detection
Distance Matrix x
Correlation Distance Matrix Cosine Distance Matrix
Distributions x
Uniform Distribution Normal Distribution Bernoulli Distribution
Engines x
mt19937 mcg59 mt2203
Moments of Low Order x
Batch Processing Online Processing Distributed Processing
Quality Metrics x
Working with the Default Metric Set Working with User-defined Quality Metrics
Working with the Default Metric Set x
Quality Metrics for Binary Classification Algorithms Quality Metrics for Multi-class Classification Algorithms Quality Metrics for Linear Regression Quality Metrics for Principal Components Analysis
Normalization x
Z-score Min-max
Optimization Solvers x
Objective Function Iterative Solver
Objective Function x
Computation Sum of Functions Mean Squared Error Algorithm Objective Function with Precomputed Characteristics Algorithm Logistic Loss Cross-entropy Loss
Iterative Solver x
Computation Limited-Memory Broyden-Fletcher-Goldfarb-Shanno Algorithm Stochastic Gradient Descent Algorithm Adaptive Subgradient Method Coordinate Descent Algorithm Stochastic Average Gradient Accelerated Method
Training and Prediction x
Decision Forest Decision Trees Gradient Boosted Trees Stump Linear and Ridge Regressions LASSO and Elastic Net Regressions k-Nearest Neighbors (kNN) Classifier Implicit Alternating Least Squares Logistic Regression Naïve Bayes Classifier Support Vector Machine Classifier Multi-class Classifier Boosting
Decision Forest x
Decision Forest Regression Decision Forest Classification Decision Forest
Decision Trees x
Decision Tree Regression Decision Tree Classification Decision Tree
Gradient Boosted Trees x
Gradient Boosted Trees Regression Gradient Boosted Trees Classification Gradient Boosted Trees
Stump x
Classification Stump Regression Stump
Linear and Ridge Regressions x
Linear Regression Ridge Regression Linear and Ridge Regressions Computation
LASSO and Elastic Net Regressions x
LASSO Elastic Net LASSO and Elastic Net Computation
Implicit Alternating Least Squares x
Batch Processing Distributed Processing Batch Processing Distributed Processing: Training Distributed Processing: Prediction of Ratings
Naïve Bayes Classifier x
Batch Processing Online Processing Distributed Processing
Boosting x
AdaBoost Classifier AdaBoost Multiclass Classifier BrownBoost Classifier LogitBoost Classifier
Services x
Extracting Version Information Handling Errors Managing Memory Managing the Computational Environment Providing a Callback for the Host Application
C++ API x
Data Management Algorithms Distributed Model: Single Process Multiple Data
Data Management x
Array Accessors Data Sources Graphs Graph Service Tables
Accessors x
Column accessor Row accessor
Data Sources x
CSV data source
Graphs x
Undirected adjacency vector graph Directed adjacency vector graph
Graph Service x
Undirected adjacency vector graph service Directed adjacency vector graph service
Tables x
Homogeneous table
Algorithms x
Clustering Covariance Decomposition Ensembles Graph Kernel Functions Nearest Neighbors (kNN) Pairwise Distances Statistics Support Vector Machines
Clustering x
DBSCAN K-Means K-Means initialization
Covariance x
Covariance
Decomposition x
Principal Components Analysis (PCA) Mathematical formulation Programming Interface Usage example Examples
Ensembles x
Decision Forest Classification and Regression (DF)
Graph x
Subgraph Isomorphism Connected Components
Kernel Functions x
Linear kernel Polynomial kernel Radial Basis Function (RBF) kernel Sigmoid kernel
Nearest Neighbors (kNN) x
k-Nearest Neighbors Classification (k-NN)
Pairwise Distances x
Minkowski distance Chebyshev distance Cosine distance
Statistics x
Basic Statistics
Support Vector Machines x
Support Vector Machine Classifier (SVM)
Distributed Model: Single Process Multiple Data x
Distributed SPMD model Communicators
Intel® oneAPI Data Analytics Library (oneDAL)

Principal Components Analysis (PCA)

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