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Data Classification
Clustering |
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| Icon | Name | Description / Applications | Modules | |
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ClusterData_KMeans | 
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Clusters data using KMeans algorithm. |
FoundationPro |
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ClusterPoints2D |
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Clusters 2D points using K Means Clustering method. |
FoundationPro |
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ClusterPoints2D_SingleLink |
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Clusters data using hierarchical single-link algorithm. |
FoundationPro |
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ClusterPoints3D |
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Clusters 3D points using K Means Clustering method. |
FoundationPro |
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FindConnectedComponents |
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Finds connected components in a graph given as set of bidirectional connections. |
FoundationPro |
Data Classification Common |
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| Icon | Name | Description / Applications | Modules | |
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CreateDataPartition |
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Divides the input set to test and train subsets, trying to maintain balance in class distribution. |
FoundationPro |
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MeasureClassificationQuality_Binary |
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Calculates classification performance metrics for binary problems. |
FoundationPro |
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MeasureClassificationQuality_Multiclass |
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Calculates classification performance metrics for multiclass problems. |
FoundationPro |
Multilayer Perceptron |
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| Icon | Name | Description / Applications | Modules | |
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MLP_Init |
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Creates multilayer perceptron model. |
FoundationPro |
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MLP_Respond |
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Calculates multilayer perceptron answer. |
FoundationPro |
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MLP_Train |
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Creates and trains multilayer perceptron classifier. |
FoundationPro |
Nearest Neighbors |
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| Icon | Name | Description / Applications | Modules | |
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KNN_Classify |
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Classify data using the KNN classifier. |
FoundationPro |
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KNN_Init |
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Initializes the KNN classifier. |
FoundationPro |
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KNN_Train |
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Trains KNN classifier using sample data. |
FoundationPro |
Principal Component Analysis |
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| Icon | Name | Description / Applications | Modules | |
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ApplyPCATransform |
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Applies previously obtained Principal Component Analysis (PCA) transformation coefficients to new data. |
FoundationPro |
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CreatePCATransform |
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Performs the Principal Component Analysis (PCA) on provided data, creates the feature vector and normalization coefficients (mean and standard deviation of variables). |
FoundationPro |
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MatrixDeterminant |
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Find the determinant of a square matrix. |
FoundationPro |
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MatrixPseudoEigenvectors |
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Find the pseudo-eigenvalues and pseudo-eigenvectors of a symmetrical square matrix. |
FoundationPro |
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NormalizeMatrixData |
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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 |
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ReversePCATransform |
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Reverses Principal Component Analysis (PCA) process. Can be used to transform data back to original feature space. |
FoundationPro |
Regression Analysis |
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| Icon | Name | Description / Applications | Modules | |
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LinearRegression | 
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Computes linear regression of given point set. |
FoundationBasic |
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LinearRegression_LTE |
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Computes linear regression of given point set using Least Trimmed Error algorithm. |
FoundationPro |
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LinearRegression_M |
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Computes linear regression of given point set using selected M-estimator for outlier suppression. |
FoundationPro |
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LinearRegression_RANSAC |
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Computes linear regression of given point set using RANSAC. |
FoundationPro |
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LinearRegression_TheilSen |
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Computes linear regression of given point set using TheilSen algorithm. |
FoundationBasic |
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QuadraticRegression |
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Computes quadratic regression of given point set. |
FoundationBasic |
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QuadraticRegression_M |
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Computes quadratic regression of given point set using selected M-estimator for outlier suppression. |
FoundationPro |
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QuadraticRegression_RANSAC |
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Computes quadratic regression of given point set using RANSAC. |
FoundationPro |
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Statistics_OfArray | 
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Computes basic statistical information out of an array of real numbers. The array must be not empty. |
FoundationBasic |
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Statistics_OfLoop |
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Computes basic statistical information out of real numbers appearing in consecutive iterations. |
FoundationBasic |
Statistics |
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| Icon | Name | Description / Applications | Modules | |
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FindDataMode_FixedCount |
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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 |
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FindDataMode_FixedSpread |
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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 |
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FindDataMode_MeanShift |
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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 |
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FindDensityMaxima_FixedCount |
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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 |
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FindDensityMaxima_FixedSpread |
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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 |
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FindMatchingRegions_IoU |
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Finds corresponding regions in two arrays based on IoU value. |
FoundationPro |
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RegionsIoU |
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Computes intersection over union value for two regions. |
FoundationPro |
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TableOfConfusion_Basic |
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Computes statistics from a confusion matrix for given TP, FP, TN, FN. |
FoundationPro |
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TableOfConfusion_BoolArray |
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Computes statistics from a confusion matrix for an array of groundTruth and results. |
FoundationPro |
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TableOfConfusion_Histograms |
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Computes confusion matrix based on two histograms and threshold value. |
FoundationPro |
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TableOfConfusion_Images |
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Computes statistics from a confusion matrix for image of groundTruth and results. |
FoundationPro |
Support Vector Machines |
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| Icon | Name | Description / Applications | Modules | |
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SVM_ClassifyMultiple |
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Classifies input points based on trained model. |
FoundationPro |
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SVM_ClassifySingle |
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Classifies input features based on a trained model. |
FoundationPro |
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SVM_Init |
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Initializes an SVM model. |
FoundationPro |
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SVM_Train |
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Trains an SVM model. |
FoundationPro |