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