Algorithms | |
 Analysis | Contains classes for analysis algorithms that are intended to uncover the underlying structure of a data set and to characterize it by a set of quantitative measures, such as statistical moments, correlations coefficients, and so on |
  Association Rules | Contains classes for the association rules algorithm. |
   Batch | |
  BACON Outlier Detection | Contains classes for computing the BACON outlier detection. |
   Batch | |
  Cholesky Decomposition | Contains classes for computing Cholesky decomposition. |
   Batch | |
  Correlation Distance Matrix | Contains classes for computing the correlation distance. |
   Batch | |
  Correlation and Variance-Covariance Matrices | Contains classes for computing the correlation or variance-covariance matrix. |
   Batch | |
   Distributed | |
   Online | |
  Cosine Distance Matrix | Contains classes for computing the cosine distance. |
   Batch | |
  Distributions | Contains classes for distributions. |
   Bernoulli Distribution | Contains classes for bernoulli distribution. |
    Batch | |
   Normal Distribution | Contains classes for normal distribution. |
    Batch | |
   Uniform Distribution | Contains classes for uniform distribution. |
    Batch | |
  Engines | Contains classes for engines. |
   Mcg59 Engine | Contains classes for mcg59 engine. |
    Batch | |
   Mt19937 Engine | Contains classes for mt19937 engine. |
    Batch | |
   Mt2203 Engine | Contains classes for mt2203 engine. |
    Batch | |
  Expectation-Maximization | Contains classes for the EM for GMM algorithm. |
   Computation | Contains classes for the EM for GMM algorithm. |
    Batch | |
   Initialization | Contains classes for the EM for GMM initialization algorithm. |
    Batch | |
  K-means Clustering | Contains classes of K-Means algorithm. |
   Computation | Contains classes of K-Means algorithm. |
    Batch | |
    Distributed | |
   Initialization | Contains classes for computing initial centroids for K-Means algorithm. |
    Batch | |
    Distributed | |
  Kernel Functions | Contains classes for computing kernel functions. |
   Linear Kernel | Contains classes for computing linear kernel functions. |
    Batch | |
   Radial Basis Function Kernel | Contains classes for computing the radial basis function (RBF) kernel. |
    Batch | |
  Math Functions | Contains classes for computing math functions. |
   Absolute Value(abs) | Contains classes for computing the absolute value function. |
    Batch | |
   Hyperbolic Tangent | Contains classes for computing the hyperbolic tangent function. |
    Batch | |
   Logistic | Contains classes for computing the logistic function. |
    Batch | |
   Rectifier Linear Unit (ReLU) | Contains classes for computing the rectified linear function. |
    Batch | |
   Smooth Rectifier Linear Unit(SmoothReLU) | Contains classes for computing smooth rectified linear unit. |
    Batch | |
   Softmax | Contains classes for computing the softmax function. |
    Batch | |
  Moments of Low Order | Contains classes for computing the results of the low order moments algorithm. |
   Batch | |
   Distributed | |
   Online | |
  Multivariate Outlier Detection | Contains classes for computing the multivariate outlier detection. |
   Batch | |
  Normalization | Contains classes to run the min-max normalization algorithms. |
   Min-max | Contains classes for computing the min-max normalization. |
    Batch | |
   Z-score | Contains classes for computing the z-score normalization. |
    Batch | |
  Optimization Solvers | Contains classes for optimization solver algorithms. |
   Adaptive Gradient Descent Algorithm | Contains classes for computing the Adaptive gradient descent. |
    Batch | |
   Iterative Solver | Contains classes for computing the iterative solver. |
    Batch | |
   Limited-Memory-Broyden-Fletcher-Goldfarb-Shanno Algorithm | Contains classes for computing the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. |
    Batch | |
   Objective Function | |
    Batch | |
    Cross-entropy loss Algorithm | Contains classes for computing the Cross-entropy loss objective function. |
     Batch | |
    Logistic loss Algorithm | Contains classes for computing the Logistic loss objective function. |
     Batch | |
    Mean Squared Error Algorithm | Contains classes for computing the Mean squared error objective function. |
     Batch | |
    Objective function with precomputed characteristics | Contains classes for the Objective function with precomputed characteristics. |
     Batch | |
    Sum of Functions | Contains classes for computing the Sum of functions. |
     Batch | |
   Stochastic Gradient Descent Algorithm | Contains classes for computing the Stochastic gradient descent. |
    Batch | |
   Stochastic average Gradient Descent Algorithm | Contains classes for computing the Coordinate descent. |
    Batch | |
  Principal Component Analysis | Contains classes for computing the results of the principal component analysis (PCA) algorithm. |
   Batch | |
   Distributed | |
   Online | |
   PCA Transformation | Contains classes for computing the results of the PCA transformation algorithm. |
    Batch | |
   Quality Metrics | Contains classes to check the quality of the pca algorithm. |
    Batch | |
    explained variance | |
     Batch | |
  QR Decomposition | Contains classes for computing the results of the QR decomposition algorithm. |
   Pivoted QR Decomposition | Contains classes for computing the pivoted QR decomposition. |
    Batch | |
   QR Decomposition without Pivoting | Contains classes for computing the results of the QR decomposition algorithm without Pivoting |
    Batch | |
    Distributed | |
    Online | |
  Quality Metrics | Contains classes for checking the quality of the classification algorithms. |
   Quality Metrics for Binary Classification Algorithms | Contains classes for computing the binary confusion matrix. |
    Batch | |
   Quality Metrics for Multi-class Classification Algorithms | Contains classes for computing the multi-class confusion matrix. |
    Batch | |
  Quantile | Contains classes to run the quantile algorithms. |
   Batch | |
  Singular Value Decomposition | Contains classes to run the singular-value decomposition (SVD) algorithm. |
   Batch | |
   Distributed | |
   Online | |
  Sorting | Contains classes to run the sorting algorithms. |
   Batch | |
  Univariate Outlier Detection | Contains classes for computing results of the univariate outlier detection algorithm. |
   Batch | |
 Base Classes | Contains classes that implement algorithms for data analysis(data mining), and data modeling(training and prediction). These algorithms include matrix decompositions, clustering algorithms, classification and regression algorithms, as well as association rules discovery. |
 Training and Prediction | Contains classes of machine learning algorithms. Unlike analysis algorithms, which are intended to characterize the structure of data sets, machine learning algorithms model the data. Modeling operates in two major stages: training and prediction or decision making |
  Base Decision Forest | Contains base classes of the decision forest algorithm |
  Base Decision Tree | Contains base classes for Decision tree algorithm |
  Base Gradient Boosted Trees | Contains base classes of the gradient boosted trees algorithm |
  Classification | Contains classes for work with the classification algorithms |
   Base Classifier | Contains base classes for working with classifiers |
    Prediction | Contains classes for making prediction based on the classifier model. |
     Batch | |
    Stump | Contains classes to work with the decision stump training algorithm. |
     Prediction | Contains classes to make prediction based on the decision stump model. |
      Batch | |
     Training | Contains classes to train the decision stump model. |
      Batch | |
    Training | Contains classes for training the model of the classification algorithms. |
     Batch | |
     Online | |
   Boosting | Contains classes to work with boosting algorithms |
    Adaboost Classifier | Contains classes for the AdaBoost classification algorithm. |
     Prediction | Contains classes for making prediction based on the AdaBoost models. |
      Batch | |
     Quality Metrics | Contains classes for checking the quality of the model trained with the AdaBoost algorithm. |
      Batch | |
     Training | Contains classes for AdaBoost models training. |
      Batch | |
    Brownboost Classifier | Contains classes for the BrownBoost classification algorithm. |
     Prediction | Contains classes for prediction based on BrownBoost models. |
      Batch | |
     Quality Metrics | Contains classes for checking the quality of the model trained with the BrownBoost algorithm. |
      Batch | |
     Training | Contains classes for BrownBoost models training. |
      Batch | |
    Logitboost Classifier | Contains classes for the LogitBoost classification algorithm. |
     Prediction | Contains classes for prediction based on LogitBoost models. |
      Batch | |
     Quality Metrics | Contains classes for checking the quality of the model trained with the LogitBoost algorithm. |
      Batch | |
     Training | Contains classes for LogitBoost models training. |
      Batch | |
    Prediction | Contains classes for prediction based on boosting models. |
     Batch | |
    Training | Contains classes for training boosting models. |
     Batch | |
    Weak Learner | Contains classes for working with weak learners. |
     Prediction | Contains classes to make predictions based on the weak learner model. |
      Batch | |
     Stump | Contains classes to work with the decision stump training algorithm. |
      Prediction | Contains classes to make prediction based on the decision stump model. |
       Batch | |
      Training | Contains classes to train the decision stump model. |
       Batch | |
     Training | Contains classes for training models of the weak learners algorithms. |
      Batch | |
   Decision Forest Classification | Contains classes for the decision_forest classification algorithm. |
    Prediction | Contains classes for prediction based on decision forest models. |
     Batch | |
    Training | Contains classes for Decision forest models training. |
     Batch | |
   Decision Tree Classification | Contains classes for Decision tree classification algorithm. |
    Prediction | Contains a class for making Decision tree model-based prediction. |
     Batch | |
    Training | Contains a class for Decision tree model-based training. |
     Batch | |
   Gradient Boosted Trees Classification | Contains classes for the gbt classification algorithm. |
    Prediction | Contains classes for prediction based on models. |
     Batch | |
    Training | Contains classes for Gradient Boosted Trees models training. |
     Batch | |
   Logistic regression | Contains classes for the logistic regression algorithm. |
    Prediction | Contains classes for prediction based on models. |
     Batch | |
    Training | Contains classes for logistic regression models training. |
     Batch | |
   Multi-class Classifier | Contains classes for computing the results of the multi-class classifier algorithm. |
    Prediction | Contains classes for prediction based on multi-class classifier models. |
     Batch | |
    Quality Metrics | Contains classes for checking the quality of the model trained with the multi-class classifier algorithm. |
     Batch | |
    Training | Contains classes for training the multi-class classifier model. |
     Batch | |
   Naive Bayes Classifier | Contains classes for multinomial Naive Bayes algorithm. |
    Prediction | Contains classes for multinomial naive Bayes model based prediction. |
     Batch | |
    Quality Metrics | Contains classes for checking the quality of the model trained with the Naive Bayes algorithm. |
     Batch | |
    Training | Contains classes for training the naive Bayes model. |
     Batch | |
     Distributed | |
     Online | |
   Support Vector Machine Classifier | Contains classes to work with the support vector machine classifier. |
    Prediction | Contains classes to make predictions based on the SVM model. |
     Batch | |
    Quality Metrics | Contains classes to check the quality of the model trained with the SVM algorithm. |
     Batch | |
    Training | Contains classes to train the SVM model. |
     Batch | |
   k-Nearest Neighbors | Contains classes for KD-tree based kNN algorithm. |
    Prediction | Contains a class for making KD-tree based kNN model-based prediction. |
     Batch | |
    Training | Contains a class for KD-tree based kNN model-based training. |
     Batch | |
  Neural Networks | Contains classes for training and prediction using neural network. |
   Initializers | Contains classes for neural network weights and biases initializers. |
    Gaussian Initializer | Contains classes for neural network weights and biases gaussian initializer. |
     Batch | |
    Truncated Gaussian Initializer | Contains classes for neural network weights and biases truncated gaussian initializer. |
     Batch | |
    Uniform Initializer | Contains classes for neural network weights and biases uniform initializer. |
     Batch | |
    Xavier Initializer | Contains classes for neural network weights and biases Xavier initializer. |
     Batch | |
   Layers | Contains classes for neural network layers. |
    Absolute Value (Abs) Layer | Contains classes of the abs layer. |
     Backward Absolute Value (Abs) Layer | Contains classes of the backward abs layer. |
      Batch | |
     Forward Absolute Value (Abs) Layer | Contains classes of the forward abs layer. |
      Batch | |
    Backward Base Layer | Contains classes for the backward stage of the neural network layer. |
    Batch Normalization Layer | Contains classes for batch normalization layer. |
     Backward Batch Normalization Layer | Contains classes for the backward batch normalization layer. |
      Batch | |
     Forward Batch Normalization Layer | Contains classes for forward batch normalization layer. |
      Batch | |
    Concat Layer | Contains classes for the concat layer. |
     Backward Concat Layer | Contains classes for the backward concat layer. |
      Batch | |
     Forward Concat Layer | Contains classes for the forward concat layer. |
      Batch | |
    Dropout Layer | Contains classes for dropout layer. |
     Backward Dropout Layer | Contains classes for the backward dropout layer. |
      Batch | |
     Forward Dropout Layer | Contains classes for the forward dropout layer. |
      Batch | |
    Element-wise Sum Layer | Contains classes for neural network element-wise sum layer. |
     Backward Element-wise Sum layer | Contains classes for backward element-wise sum layer. |
      Batch | |
     Forward Element-wise Sum Layer | Contains classes for the forward element-wise sum layer. |
      Batch | |
    Exponential Linear Unit (ELU) Layer | Contains classes for the ELU layer. |
     Backward Exponential Linear Unit (ELU) Layer | Contains classes for the backward ELU layer. |
      Batch | |
     Forward Exponential Linear Unit (ELU) Layer | Contains classes for the forward ELU layer. |
      Batch | |
    Forward Base Layer | Contains classes for the forward stage of the neural network layer. |
    Fully-connected Layer | Contains classes for neural network fully-connected layer. |
     Backward Fully-connected Layer | Contains classes for backward fully-connected layer. |
      Batch | |
     Forward Fully-connected Layer | Contains classes for the forward fully-connected layer. |
      Batch | |
    Hyperbolic Tangent Layer | Contains classes for the hyperbolic tangent layer. |
     Backward Hyperbolic Tangent Layer | Contains classes for the backward hyperbolic tangent layer. |
      Batch | |
     Forward Hyperbolic Tangent Layer | Contains classes for the forward hyperbolic tangent layer. |
      Batch | |
    Local Response Normalization Layer | Contains classes for local response normalization layer. |
     Backward Local Response Normalization Layer | Contains classes for the backward local response normalization layer. |
      Batch | |
     Forward Local Response Normalization Layer | Contains classes for the forward local response normalization layer. |
      Batch | |
    Local contrast normalization (LCN) Layer | Contains classes for neural network local contrast normalization layer. |
     Backward Local contrast normalization (LCN) Layer | Contains classes for the backward local contrast normalization layer. |
      Batch | |
     Forward Local contrast normalization (LCN) Layer | Contains classes for the forward local contrast normalization layer. |
      Batch | |
    Logistic Layer | Contains classes for the logistic layer. |
     Backward Logistic Layer | Contains classes for the backward logistic layer. |
      Batch | |
     Forward Logistic Layer | Contains classes for the forward logistic layer. |
      Batch | |
    Loss Layer | Contains classes for loss layer. |
     Backward Loss Layer | Contains classes for the backward loss layer. |
      Batch | |
     Forward Loss Layer | Contains classes for the forward loss layer. |
      Batch | |
     Logistic Cross-entropy Layer | Contains classes for logistic cross-entropy layer. |
      Backward Logistic Cross-entropy Layer | Contains classes for the backward logistic cross-entropy layer. |
       Batch | |
      Forward Logistic Cross-entropy Layer | Contains classes for the forward logistic cross-entropy layer. |
       Batch | |
     Softmax Cross-entropy Layer | Contains classes for softmax cross-entropy layer. |
      Backward Softmax Cross-entropy Layer | Contains classes for the backward softmax cross-entropy layer. |
       Batch | |
      Forward Softmax Cross-entropy Layer | Contains classes for the forward softmax cross-entropy layer. |
       Batch | |
    One-dimensional Pooling Layer | Contains classes for the one-dimensional (1D) pooling layer. |
     Backward One-dimensional Pooling Layer | Contains classes for backward one-dimensional (1D) pooling layer. |
     Forward One-dimensional Pooling Layer | Contains classes for the forward one-dimensional (1D) pooling layer. |
     One-dimensional Average Pooling Layer | Contains classes for average one-dimensional (1D) pooling layer. |
      Backward One-dimensional Average Pooling Layer | Contains classes for backward average 1D pooling layer. |
       Batch | |
      Forward One-dimensional Average Pooling Layer | Contains classes for forward average 1D pooling layer. |
       Batch | |
     One-dimensional Max Pooling Layer | Contains classes for maximum one-dimensional (1D) pooling layer. |
      Backward One-dimensional Max Pooling Layer | Contains classes for backward maximum 1D pooling layer. |
       Batch | |
      Forward One-dimensional Max Pooling Layer | Contains classes for forward maximum 1D pooling layer. |
       Batch | |
    Parametric Rectifier Linear Unit (pReLU) Layer | Contains classes for the prelu layer. |
     Backward Parametric Rectifier Linear Unit (pReLU) Layer | Contains classes for the backward prelu layer. |
      Batch | |
     Forward Parametric Rectifier Linear Unit (pReLU) Layer | Contains classes for the forward prelu layer. |
      Batch | |
    Rectifier Linear Unit (ReLU) Layer | Contains classes for the relu layer. |
     Backward Rectifier Linear Unit (ReLU) Layer | Contains classes for the backward relu layer. |
      Batch | |
     Forward Rectifier Linear Unit (ReLU) Layer | Contains classes for the forward relu layer. |
      Batch | |
    Reshape Layer | Contains classes of the reshape layer. |
     Backward Reshape Layer | Contains classes of the backward reshape layer. |
      Batch | |
     Forward Reshape Layer | Contains classes of the forward reshape layer. |
      Batch | |
    Smooth Rectifier Linear Unit (SmoothReLU) Layer | Contains classes for smooth relu layer. |
     Backward Smooth Rectifier Linear Unit (SmoothReLU) Layer | Contains classes for the backward smooth relu layer. |
      Batch | |
     Forward Smooth Rectifier Linear Unit (SmoothReLU) Layer | Contains classes for the forward smooth relu layer. |
      Batch | |
    Softmax Layer | Contains classes of the softmax layer. |
     Backward Softmax Layer | Contains classes of the backward softmax layer. |
      Batch | |
     Forward Softmax Layer | Contains classes of the forward softmax layer. |
      Batch | |
    Split Layer | Contains classes for the split layer. |
     Backward Split Layer | Contains classes for the backward split layer. |
      Batch | |
     Forward Split Layer | Contains classes for the forward split layer. |
      Batch | |
    Three-dimensional Pooling Layer | Contains classes for the three-dimensional (3D) pooling layer. |
     Backward Three-dimensional Pooling Layer | Contains classes for backward three-dimensional (3D) pooling layer. |
     Forward Three-dimensional Pooling Layer | Contains classes for the forward three-dimensional (3D) pooling layer. |
     Three-dimensional Average Pooling Layer | Contains classes for average three-dimensional (3D) pooling layer. |
      Backward Three-dimensional Average Pooling Layer | Contains classes for backward average 3D pooling layer. |
       Batch | |
      Forward Three-dimensional Average Pooling Layer | Contains classes for forward average 3D pooling layer. |
       Batch | |
     Three-dimensional Max Pooling Layer | Contains classes for maximum three-dimensional (3D) pooling layer. |
      Backward Three-dimensional Max Pooling Layer | Contains classes for backward maximum 3D pooling layer. |
       Batch | |
      Forward Three-dimensional Max Pooling Layer | Contains classes for forward maximum 3D pooling layer. |
       Batch | |
    Two-dimensional Convolution Layer | Contains classes for neural network 2D convolution layer. |
     Backward Two-dimensional Convolution Layer | Contains classes for the backward 2D convolution layer. |
      Batch | |
     Forward Two-dimensional Convolution Layer | Contains classes for the forward 2D convolution layer. |
      Batch | |
    Two-dimensional Locally Connected Layer | Contains classes for neural network 2D locally connected layer. |
     Backward Two-dimensional Locally Connected Layer | Contains classes for the backward 2D locally connected layer. |
      Batch | |
     Forward Two-dimensional Locally Connected Layer | Contains classes for the forward 2D locally connected layer. |
      Batch | |
    Two-dimensional Pooling Layer | Contains classes for the two-dimensional (2D) pooling layer. |
     Backward Two-dimensional Pooling Layer | Contains classes for backward two-dimensional (2D) pooling layer. |
     Forward Two-dimensional Pooling Layer | Contains classes for the forward two-dimensional (2D) pooling layer. |
     Two-dimensional Average Pooling Layer | Contains classes for average two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Average Pooling Layer | Contains classes for backward average 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Average Pooling Layer | Contains classes for forward average 2D pooling layer. |
       Batch | |
     Two-dimensional Max Pooling Layer | Contains classes for maximum two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Max Pooling Layer | Contains classes for backward maximum 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Max Pooling Layer | Contains classes for forward maximum 2D pooling layer. |
       Batch | |
     Two-dimensional Stochastic Pooling Layer | Contains classes for stochastic two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Stochastic Pooling Layer | Contains classes for backward stochastic 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Stochastic Pooling Layer | Contains classes for forward stochastic 2D pooling layer. |
       Batch | |
    Two-dimensional Spatial Pyramid Pooling Layer | Contains classes for the two-dimensional (2D) spatial layer. |
     Backward Two-dimensional Spatial Pyramid Pooling Layer | Contains classes for backward two-dimensional (2D) spatial layer. |
     Forward Two-dimensional Spatial Pyramid Pooling Layer | Contains classes for the forward two-dimensional (2D) spatial layer. |
     Two-dimensional Spatial pyramid average Pooling Layer | Contains classes for spatial pyramid average two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Spatial pyramid average Pooling Layer | Contains classes for backward spatial pyramid average 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Spatial pyramid average Pooling Layer | Contains classes for forward spatial pyramid average 2D pooling layer. |
       Batch | |
     Two-dimensional Spatial pyramid maximum Pooling Layer | Contains classes for spatial pyramid maximum two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Spatial pyramid maximum Pooling Layer | Contains classes for backward spatial pyramid maximum 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Spatial pyramid maximum Pooling Layer | Contains classes for forward spatial pyramid maximum 2D pooling layer. |
       Batch | |
     Two-dimensional Spatial pyramid stochastic Pooling Layer | Contains classes for spatial pyramid stochastic two-dimensional (2D) pooling layer. |
      Backward Two-dimensional Spatial pyramid stochastic Pooling Layer | Contains classes for backward spatial pyramid stochastic 2D pooling layer. |
       Batch | |
      Forward Two-dimensional Spatial pyramid stochastic Pooling Layer | Contains classes for forward spatial pyramid stochastic 2D pooling layer. |
       Batch | |
    Two-dimensional Transposed Convolution Layer | Contains classes for neural network 2D transposed convolution layer. |
     Backward Two-dimensional Transposed Convolution Layer | Contains classes for the backward 2D transposed convolution layer. |
      Batch | |
     Forward Two-dimensional Transposed Convolution Layer | Contains classes for the forward 2D transposed convolution layer. |
      Batch | |
   Prediction | Contains classes for making prediction based on the trained model. |
    Batch | |
   Training | Contains classes for training the model of the neural network. |
    Batch | |
    Distributed | |
  Recommendation Systems | Contains classes to work with recommendation systems |
   Implicit Alternating Least Squares | Contains classes of the implicit ALS algorithm. |
    Prediction | Contains classes for making implicit ALS model-based prediction. |
     Batch | |
     Distributed | |
    Training | Contains classes of the implicit ALS training algorithm. |
     Batch | |
     Distributed | |
     Initialization | Contains classes for the implicit ALS initialization algorithm. |
      Batch | |
      Distributed | |
  Regression | Contains classes for work with the regression algorithms |
   Base Regression | Contains base classes for the regression algorithms. |
    Prediction | Contains a class for making the regression model-based prediction. |
     Batch | |
    Training | Contains a class for regression model-based training. |
     Batch | |
     Online | |
   Decision Forest Regression | Contains classes for decision forest regression algorithm. |
    Prediction | Contains a class for making decision forest model-based prediction. |
     Batch | |
    Training | Contains a class for decision forest model-based training. |
     Batch | |
   Decision Tree for Regression | Contains classes for decision tree regression algorithm. |
    Prediction | Contains a class for making Decision tree model-based prediction. |
     Batch | |
    Training | Contains a class for Decision tree model-based training. |
     Batch | |
   Gradient Boosted Trees Classification | Contains classes for the gbt classification algorithm. |
    Prediction | Contains classes for prediction based on models. |
     Batch | |
    Training | Contains classes for Gradient Boosted Trees models training. |
     Batch | |
   Gradient Boosted Trees Regression | Contains classes for gradient boosted trees regression algorithm. |
    Prediction | Contains a class for making model-based prediction. |
     Batch | |
    Training | Contains a class for model-based training. |
     Batch | |
   Linear Model | Contains base classes of regression algorithms with linear model |
    Elastic Net | Contains classes of the elastic net algorithm. |
     Prediction | Contains a class for making elastic net model-based prediction. |
      Batch | |
     Training | Contains a class for elastic net model-based training. |
      Batch | |
    LASSO Regression | Contains classes of the lasso regression algorithm. |
     Prediction | Contains a class for making lasso regression model-based prediction. |
      Batch | |
     Training | Contains a class for lasso regression model-based training. |
      Batch | |
    Linear Regression | Contains classes of the linear regression algorithm. |
     Prediction | Contains a class for making linear regression model-based prediction. |
      Batch | |
     Quality Metrics | Contains classes to check the quality of the model trained with the linear regression algorithm. |
      Batch | |
      Group of Beta Coefficients | |
       Batch | |
      Single Beta Coefficient | |
       Batch | |
     Training | Contains a class for linear regression model-based training. |
      Batch | |
      Distributed | |
      Online | |
    Prediction | Contains a class for making the regression model-based prediction. |
     Batch | |
    Ridge Regression | Contains classes of the ridge regression algorithm. |
     Prediction | Contains a class for making ridge regression model-based prediction. |
      Batch | |
     Training | Contains a class for ridge regression model-based training. |
      Batch | |
      Distributed | |
      Online | |
    Training | Contains a class for regression model-based training. |
     Batch | |
     Online | |
   Stump | Contains classes to work with the decision stump training algorithm. |
    Prediction | Contains classes to make prediction based on the decision stump model. |
     Batch | |
    Training | Contains classes to train the decision stump model. |
     Batch | |
   Tree regression | |
  Tree utils | Contains classes for work with the tree-based algorithms |
Computation | Contains classes of the DBSCAN algorithm. |
 Batch | |
 Distributed | |
Data Management | Contains classes that implement data management functionality, including NumericTables, DataSources, and Compression. |
 Data Compression | Contains classes for data compression and decompression |
 Data Dictionaries | Contains classes that represent a dictionary of a data set and provide methods to work with the data dictionary |
 Data Model | Contains classes that provide functionality of Collection container for objects derived from SerializationIface interface and implements SerializationIface itself |
 Data Serialization and Deserialization | Contains classes that implement serialization and deserialization |
 Data Sources | Specifies methods to access data |
  Modifiers | Defines special components which can be used to modify data during the loading through the data source components |
   CSV | Defines CSV specific feature modifiers |
   SQL | Defines SQL specific feature modifiers |
 Numeric Tables | Contains classes for a data management component responsible for representation of data in the numeric format |
 Numeric Tensors | Contains classes for a data management component responsible for representation of data in the n-dimensions numeric format |
Prediction | Contains classes to make prediction based on the decision stump model. |
 Batch | |
Prediction | Contains classes to make prediction based on the decision stump model. |
 Batch | |
Services | Contains classes that implement service functionality, including error handling, memory allocation, and library version information. |
 Extracting Version Information | Provides information about the version of Intel(R) Data Analytics Acceleration Library |
 Handling Errors | Contains classes and methods to handle exceptions or errors that can occur during library operation |
 Managing Memory | Contains classes that implement memory allocation and deallocation |
 Managing the Computational Environment | Provides methods to interact with the environment, including processor detection and control by the number of threads |
Stochastic average Gradient Descent Algorithm | Contains classes for computing the Stochastic average gradient descent. |
 Batch | |
Training | Contains classes to train the decision stump model. |
 Batch | |
Training | Contains classes to train the decision stump model. |
 Batch | |