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ENVIMachineLearningModel
| This function restores an ENVIMachineLearningModel object, which specifies the MachineLearning model used for machine learning. |
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ENVIMachineLearningModel::Close
| This method closes the ENVIMachineLearningModel object. |
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ENVIMachineLearningModel::Dehydrate
| Returns a hash describing this object. |
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ENVITensorFlowModel::Hydrate
| Use the Hydrate static function method to create the object from its dehydrated from. |
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MachineLearningClassification Task
| This task performs classification for all ENVI Machine Learning model types. |
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MachineLearningEvaluateClassifier Task
| This task evaluates a classifier using labeled rasters that may or may not have been used during training. |
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MLTrainingDataFromROIs Task
| This task builds a spectral raster from an input raster and ROIs for use with ENVI Machine Learning routines. |
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MLTrainingDataFromSpectralLibrary Task
| This task builds a training raster from an input raster and a Spectral Library for use with ENVI Machine Learning training tasks. |
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NormalizationStatistics Task
| This task outputs global normalization statistics from an aggregate of rasters. |
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Programming Routines and Tasks
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TrainBirch Task
| This task executes an unsupervised BIRCH algorithm against the provided input training rasters. |
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TrainExtraTrees Task
| This task implements a meta estimator that fits several randomized decision trees (i.e., extra-trees) on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. |
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TrainIsolationForest Task
| This task executes the Isolation Forest anomaly detection algorithm against the provided input training rasters. |
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TrainKNeighbors Task
| This task implements learning based on the k nearest neighbors of each query point, where k is an integer value specified by the user in the form of ROI class values. |
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TrainLinearSVM Task
| This task divides a dataset into a number of classes in order to find a maximum marginal hyperplane. |
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TrainLocalOutlierFactor Task
| This task detects the samples that have a substantially lower density than its neighbors and labels the detections as anomalies. |
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TrainMiniBatchKMeans Task
| This task executes an unsupervised Mini Batch K-Means algorithm against the provided input training rasters. |
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TrainNaiveBayes Task
| This task applies Bayes theorem with a strong assumption that all the predictors are independent to each other; i.e., the presence of a feature in a class is independent to the presence of any other feature in the same class. |
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TrainRandomForest Task
| This task creates a set of decision trees from a randomly selected subset of the training set. |
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TrainRBFSVM Task
| This task executes the Radial Basis Function Support Vector Classification algorithm against the provided input training rasters. |