SAS Visual Data Mining and Machine Learning
Note: Some of the other products in SAS Viya support additional action sets, which are available
in their product-specific list of action sets. The action sets that are provided by
SAS Visual
Data Mining and Machine Learning are included in the following table:
| Action Set | Syntax Name | Description |
|---|---|---|
| Access Control | accessControl | Provides actions for managing user access to resources |
| Active Machine Learning | activeLearn | Provides an action set for performing active learning which interactively query the user in order to minimize the labeling effort |
| Aggregation | aggregation | Provides actions for aggregating the values of one or more variables |
| Analytic Store Scoring | aStore | Provides actions for scoring using an analytic store |
| Association Rule Mining | ruleMining | Provides actions for association rule mining |
| Audio | audio | Provides actions for processing audio data |
| Autotune | autotune | Provides actions to tune machine learning algorithm hyperparameters for individual or multiple model types |
| Bayesian Net Classifier | bayesianNetClassifier | Uses Bayesian network models to classify the target variable |
| BioMedImage | bioMedImage | Provides actions for biomedical image processing |
| Boolean Rule | boolRule | Provides actions for Boolean rule extraction and scoring |
| Builtins | builtins | Provides actions that enable server management |
| Cardinality Analysis | cardinality | Provides actions for evaluating data cardinality |
| CASL Server | sccasl | Provides actions for running server-side CASL code |
| Clustering | clustering | Provides actions for clustering |
| Data Preprocess | dataPreprocess | Provides actions for data preprocessing and transformation |
| Data Science Pilot | dataSciencePilot | Provides actions for automating data science workflows, including automatic machine learning pipeline exploration, execution and ranking. |
| Data Shaping | dataShaping | Provides actions for reshaping wide or long tables. |
| DATA Step | dataStep | Provides actions for running a SAS DATA step |
| Decision Tree | decisionTree | Provides actions for modeling and scoring with decision trees, forests, and gradient boosting |
| Deep Learning | deepLearn | Provides a superset of actions for modeling and scoring with deep neural (DNN), convolutional (CNN), and recurrent (RNN) networks |
| Deep Neural Network | deepNeural | Provides actions for modeling and scoring with fully connected deep neural networks (DNN) |
| Dimension Reduction | varReduce | Provides actions for performing supervised and unsupervised dimension reduction |
| Distribution System Simulation | simSystem | Provides actions for simulating data from systems of distributions |
| DS2 | ds2 | Provides actions for preparing and executing DS2 programs |
| Duplicate Management | deduplication | Provides an action for managing rows within groups |
| Explain Model | explainModel | Provides actions for explaining already trained models. |
| Factorization Machine | factmac | Provides actions for factorization machines |
| Fair AI Tools | fairAITools | Provides action for calculating bias metrics for predictive models. |
| Fast k-Nearest Neighbor | fastKnn | Provides actions for the k-nearest neighbor algorithm |
| FCMP | fcmpact | Provides actions that add and run FCMP code |
| FedSQL | fedSql | Provides actions for submitting SQL statements |
| Frequency and Crosstabulation Analysis | freqTab | Provides actions for performing frequency and crosstabulation analysis |
| Generalized Additive Models | gam | Provides actions for fitting Generalized Additive Models |
| Generalized Linear Multitask Learning | gleam | Implements generalized linear multitask learning and solves multiple related sparse linear regression problems simultaneously |
| Generative Adversarial Network Action Set | generativeAdversarialNet | Provides actions for training generative adversarial network models. |
| Graph-Based Semisupervised Learning | graphSemiSupLearn | Provides actions for graph-based semisupervised learning |
| Graphical Variable Clustering | gVarCluster | Provides an action for performing variable clustering and providing undirected network for mining relationship among variables |
| Hypergroup | hyperGroup | hyperGroup: Find hypergroups, graph layouts, colors, communities, centralities, shortests paths, and create structural and nBody graphs. thePlotThickens: used to scatter-plot or geo-cluster a large number of points. |
| Image | image | Provides actions for image processing |
| Independent Component Analysis | ica | Provides actions for performing independent component analysis |
| Kernel Principal Component Analysis | kernelPca | Provides actions for kernel principal component analysis |
| Language Model | langModel | Provides actions that are used for language models in speech-to-text systems. |
| Light Gradient Boosting | lightGradBoost | Provides actions for performing light gradient boosting. |
| Machine Learning for Sparse Data | sparseML | Provides actions for sparse data learning |
| Machine Learning Tools | mlTools | Provides utility actions for machine learning |
| Mixed Modeling | mixed | Provides actions for fitting mixed models |
| Model Publishing and Scoring | modelPublishing | Provides actions to support DATA step and DS2 model publishing and scoring in CAS and in external databases |
| Model-Based Clustering | mbc | Provides actions for performing model-based clustering |
| Network | network | Provides actions for network analysis |
| Neural Network | neuralNet | Provides actions for training and scoring artificial neural networks |
| Nonlinear Models | nonlinear | Provides actions for fitting nonlinear models |
| Nonnegative Matrix Factorization | nmf | Provides actions for performing nonnegative matrix factorization |
| Nonparametric Bayes | nonParametricBayes | Nonparametric Bayes |
| Partial Least Squares | pls | Provides actions for fitting reduced-rank linear models, including partial least squares |
| Percentile | percentile | Provides actions for calculating percentiles, boxplot values, and assessing models |
| Principal Component Analysis | pca | Provides actions for performing principal component analysis |
| Proportional Hazards Regression Modeling | phreg | Provides actions for fitting proportional hazards model |
| Quantile Regression Modeling | quantreg | Provides actions for performing quantile regression |
| Recommender System | recommend | Provides actions for building a recommender system |
| Recurrent Neural Network | deepRnn | Provides actions for modeling and scoring with deep recurrent neural networks (RNN) with raw text inputs |
| Regression | regression | Provides actions for fitting linear, generalized linear, and logistic models |
| Reinforcement Learning | reinforcementLearn | Provides actions for building, training, and scoring reinforcement learning models |
| Risk Modeling and Decisioning | riskmd | Provides actions for risk modeling and decisioning |
| Robust PCA | robustPca | Provides actions for robust principal component analysis (RPCA) and moving windows principal component analysis (MWPCA) |
| Sampling and Partitioning | sampling | Provides actions for sampling and partitioning of data |
| SAS Embedded Process for Spark | sparkEmbeddedProcess | Provides actions for interacting with the SAS Embedded Process for Spark continuous session |
| Search | search | Provides actions for indexing structured and unstructured data, querying against an index, and performing aggregations on an index |
| Sentiment Analysis | sentimentAnalysis | Provides actions for the SAS Sentiment Analysis Application in CAS |
| Sequence Rule Mining | sequence | Provides actions for sequence rule mining |
| Server Properties | configuration | Provides actions for managing server options |
| Session Methods | session | Provides actions to display session information and manage sessions |
| Session Properties | sessionProp | Provides actions for managing session properties |
| Simple Analytics | simple | Provides actions for performing basic analytic functions |
| Sparse Regression | sandwich | Provides action for fitting sparse regression models |
| Statistical Process Control | spc | Provides actions for control chart analysis |
| Support Vector Data Description | svDataDescription | Provides actions for anomaly detection |
| Support Vector Machine | svm | Provides actions for support vector machines |
| t-Distributed Stochastic Neighbor Embedding | tSne | Provides actions for the t-distributed stochastic neighbor embedding algorithm |
| Table | table | Provides actions for accessing and managing data |
| Text Mining | textMining | Provides actions for mining textual data |
| Transpose | transpose | Provides actions for transposing data |
Last updated: February 2, 2022