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Data Classification

Clustering

Icon Name Description / Applications Modules
ClusterData_KMeans

Clusters data using KMeans algorithm.

FoundationPro
ClusterPoints2D

Clusters 2D points using K Means Clustering method.

FoundationPro
ClusterPoints2D_SingleLink

Clusters data using hierarchical single-link algorithm.

FoundationPro
ClusterPoints3D

Clusters 3D points using K Means Clustering method.

FoundationPro
FindConnectedComponents

Finds connected components in a graph given as set of bidirectional connections.

FoundationPro

Data Classification Common

Icon Name Description / Applications Modules
CreateDataPartition

Divides the input set to test and train subsets, trying to maintain balance in class distribution.

FoundationPro
MeasureClassificationQuality_Binary

Calculates classification performance metrics for binary problems.

FoundationPro
MeasureClassificationQuality_Multiclass

Calculates classification performance metrics for multiclass problems.

FoundationPro

Multilayer Perceptron

Icon Name Description / Applications Modules
MLP_Init

Creates multilayer perceptron model.

FoundationPro
MLP_Respond

Calculates multilayer perceptron answer.

FoundationPro
MLP_Train

Creates and trains multilayer perceptron classifier.

FoundationPro

Nearest Neighbors

Icon Name Description / Applications Modules
KNN_Classify

Classify data using the KNN classifier.

FoundationPro
KNN_Init

Initializes the KNN classifier.

FoundationPro
KNN_Train

Trains KNN classifier using sample data.

FoundationPro

Principal Component Analysis

Icon Name Description / Applications Modules
ApplyPCATransform

Applies previously obtained Principal Component Analysis (PCA) transformation coefficients to new data.

FoundationPro
CreatePCATransform

Performs the Principal Component Analysis (PCA) on provided data, creates the feature vector and normalization coefficients (mean and standard deviation of variables).

FoundationPro
MatrixDeterminant

Find the determinant of a square matrix.

FoundationPro
MatrixPseudoEigenvectors

Find the pseudo-eigenvalues and pseudo-eigenvectors of a symmetrical square matrix.

FoundationPro
NormalizeMatrixData

Treats Matrix as a data frame, where examples are in rows while columns represent features, and normalizes the data by subtracting mean from each column and dividing it by its standard deviation.

FoundationPro
ReversePCATransform

Reverses Principal Component Analysis (PCA) process. Can be used to transform data back to original feature space.

FoundationPro

Regression Analysis

Icon Name Description / Applications Modules
LinearRegression

Computes linear regression of given point set.

FoundationBasic
LinearRegression_LTE

Computes linear regression of given point set using Least Trimmed Error algorithm.

FoundationPro
LinearRegression_M

Computes linear regression of given point set using selected M-estimator for outlier suppression.

FoundationPro
LinearRegression_RANSAC

Computes linear regression of given point set using RANSAC.

FoundationPro
LinearRegression_TheilSen

Computes linear regression of given point set using TheilSen algorithm.

FoundationBasic
QuadraticRegression

Computes quadratic regression of given point set.

FoundationBasic
QuadraticRegression_M

Computes quadratic regression of given point set using selected M-estimator for outlier suppression.

FoundationPro
QuadraticRegression_RANSAC

Computes quadratic regression of given point set using RANSAC.

FoundationPro
Statistics_OfArray

Computes basic statistical information out of an array of real numbers. The array must be not empty.

FoundationBasic
Statistics_OfLoop

Computes basic statistical information out of real numbers appearing in consecutive iterations.

FoundationBasic

Statistics

Icon Name Description / Applications Modules
FindDataMode_FixedCount

Finds the mode in a set of data values by looking for highest concentration of a fixed number of samples.


Can be used to determine a histogram maximum without actually creating the histogram.

FoundationPro
FindDataMode_FixedSpread

Finds the mode in a set of data values by looking for highest number of samples withing the specified spread.


Can be used to determine a histogram maximum without actually creating the histogram.

FoundationPro
FindDataMode_MeanShift

Finds the mode in a set of data values by iteratively computing its median.


Can be used to determine a histogram maximum without actually creating the histogram.

FoundationPro
FindDensityMaxima_FixedCount

Finds local density maxima in set of values by looking for the highest concentration of a fixed number of samples.


Can be used to determine histogram's local maxima without actually creating the histogram.

FoundationPro
FindDensityMaxima_FixedSpread

Finds local density maxima in a set of values by looking for the highest number of samples withing a range determined by the given spread.


Can be used to determine histogram's local maxima without actually creating the histogram.

FoundationPro
FindMatchingRegions_IoU

Finds corresponding regions in two arrays based on IoU value.

FoundationPro
RegionsIoU

Computes intersection over union value for two regions.

FoundationPro
TableOfConfusion_Basic

Computes statistics from a confusion matrix for given TP, FP, TN, FN.

FoundationPro
TableOfConfusion_BoolArray

Computes statistics from a confusion matrix for an array of groundTruth and results.

FoundationPro
TableOfConfusion_Histograms

Computes confusion matrix based on two histograms and threshold value.

FoundationPro
TableOfConfusion_Images

Computes statistics from a confusion matrix for image of groundTruth and results.

FoundationPro

Support Vector Machines

Icon Name Description / Applications Modules
SVM_ClassifyMultiple

Classifies input points based on trained model.

FoundationPro
SVM_ClassifySingle

Classifies input features based on a trained model.

FoundationPro
SVM_Init

Initializes an SVM model.

FoundationPro
SVM_Train

Trains an SVM model.

FoundationPro