• Data Access
• Copy Repository Entry
• Delete Repository Entry
• Move Repository Entry
• Rename Repository Entry
• Retrieve
• Store
• Files
• Read
• Read ARFF
• Read Access
• Read BibTeX
• Read C4.5
• Read CSV
• Read DBase
• Read DasyLab
• Read Excel
• Read SAS
• Read SPSS
• Read Sparse
• Read Stata
• Read URL
• Read XML
• Read XRFF
• Write
• Write ARFF
• Write Access
• Write CSV
• Write Excel
• Write PMML
• Write Special Format
• Write XRFF
• Database
• Read Database
• Update Database
• Write Database
• NoSQL
• Cassandra
• Delete Cassandra
• Execute CQL
• Read Cassandra
• Write Cassandra
• MongoDB
• Delete MongoDB
• Execute MongoDB Command
• Read MongoDB
• Update MongoDB
• Write MongoDB
• Solr
• Add to Solr (Data)
• Add to Solr (Documents)
• Search Solr (Data)
• Search Solr (Documents)
• Applications
• Trigger Zapier
• Salesforce
• Delete Salesforce
• Read Salesforce
• Update Salesforce
• Write Salesforce
• Mozenda
• Read Mozenda
• Qlik
• Write QVX
• Twitter
• Get Twitter Relations
• Get Twitter User Details
• Get Twitter User Statuses
• Search Twitter
• Splunk
• Search Splunk
• Cloud Storage
• Amazon S3
• Loop Amazon S3
• Read Amazon S3
• Write Amazon S3
• Azure Blob Storage
• Delete Azure Blob Storage Resource
• Loop Azure Blob Storage
• Read Azure Blob Storage
• Write Azure Blob Storage
• Azure Data Lake Storage Gen1
• Delete Azure Data Lake Storage Resource
• Loop Azure Data Lake Storage
• Read Azure Data Lake Storage
• Write Azure Data Lake Storage
• Azure Data Lake Storage Gen2
• Delete Azure Data Lake Storage Gen2 Resource
• Loop Azure Data Lake Storage Gen2
• Read Azure Data Lake Storage Gen2
• Write Azure Data Lake Storage Gen2
• Dropbox
• Read Dropbox
• Write Dropbox
• Google Storage
• Loop Google Storage
• Read Google Storage
• Write Google Storage
• Blending
• Python Transformer
• Attributes
• Reorder Attributes
• Names & Roles
• Rename
• Rename by Constructions
• Rename by Example Values
• Rename by Generic Names
• Rename by Replacing
• Set Role
• Types
• Date to Nominal
• Date to Numerical
• Format Numbers
• Guess Types
• Nominal to Binominal
• Nominal to Date
• Nominal to Numerical
• Nominal to Text
• Numerical to Binominal
• Numerical to Date
• Numerical to Polynominal
• Numerical to Real
• Parse Numbers
• Real to Integer
• Set Positive Value
• Text to Nominal
• Selection
• Remove Attribute Range
• Remove Correlated Attributes
• Remove Useless Attributes
• Select Attributes
• Select by Random
• Select by Weights
• Work on Subset
• Generation
• Generate Absolutes
• Generate Aggregation
• Generate Attributes
• Generate Concatenation
• Generate Copy
• Generate Empty Attribute
• Generate Function Set
• Generate Gaussians
• Generate ID
• Generate Item Set Indicators
• Generate Products
• Generate TFIDF
• Generate Weight (LPR)
• Generate Weight (Stratification)
• Examples
• Filter
• Filter Example Range
• Filter Examples
• Sampling
• Sample
• Sample (Bootstrapping)
• Sample (Kennard-Stone)
• Sample (Model-Based)
• Sample (Stratified)
• Split Data
• Sort
• Shuffle
• Sort
• Sort by Pareto Rank
• Table
• Grouping
• Aggregate
• Rotation
• De-Pivot
• Pivot
• Transpose
• Joins
• Append
• Cartesian Product
• Intersect
• Join
• Set Minus
• Superset
• Union
• Values
• Add
• Adjust Date
• Cut
• Map
• Merge
• Remap Binominals
• Replace
• Replace (Dictionary)
• Set Data
• Split
• Trim
• Cleansing
• Normalization
• De-Normalize
• Normalize
• Scale by Weights
• Binning
• Discretize by Binning
• Discretize by Entropy
• Discretize by Frequency
• Discretize by Size
• Discretize by User Specification
• Missing
• Declare Missing Value
• Fill Data Gaps
• Impute Missing Values
• Remove Unused Values
• Replace Infinite Values
• Replace Missing Values
• Duplicates
• Remove Duplicates
• Outliers
• Detect Outlier (COF)
• Detect Outlier (Densities)
• Detect Outlier (Distances)
• Detect Outlier (LOF)
• Dimensionality Reduction
• Independent Component Analysis
• Principal Component Analysis
• Principal Component Analysis (Kernel)
• Self-Organizing Map
• Singular Value Decomposition
• Modeling
• Python Learner
• Predictive
• Create Formula
• Group Models
• Ungroup Models
• Update Model
• Lazy
• Default Model
• k-NN
• Bayesian
• Naive Bayes
• Naive Bayes (Kernel)
• Trees
• CHAID
• Decision Stump
• Decision Tree
• Decision Tree (Multiway)
• Decision Tree (Weight-Based)
• Gradient Boosted Trees
• ID3
• Random Forest
• Random Tree
• Rules
• Rule Induction
• Single Rule Induction
• Single Rule Induction (Single Attribute)
• Subgroup Discovery
• Tree to Rules
• Neural Nets
• AutoMLP
• Deep Learning
• Neural Net
• Perceptron
• Functions
• Gaussian Process
• Generalized Linear Model
• Linear Regression
• Local Polynomial Regression
• Polynomial Regression
• Relevance Vector Machine
• Seemingly Unrelated Regression
• Vector Linear Regression
• Logistic Regression
• Logistic Regression
• Logistic Regression (Evolutionary)
• Logistic Regression (SVM)
• Support Vector Machines
• Fast Large Margin
• Hyper Hyper
• Support Vector Machine
• Support Vector Machine (Evolutionary)
• Support Vector Machine (LibSVM)
• Support Vector Machine (Linear)
• Support Vector Machine (PSO)
• Discriminant Analysis
• Linear Discriminant Analysis
• Quadratic Discriminant Analysis
• Regularized Discriminant Analysis
• Ensembles
• AdaBoost
• Additive Regression
• Bagging
• Bayesian Boosting
• Classification by Regression
• Find Threshold (Meta)
• Hierarchical Classification
• MetaCost
• Multi Label Modeling
• Polynominal by Binominal Classification
• Relative Regression
• Stacking
• Subgroup Discovery (Meta)
• Transformed Regression
• Vote
• Segmentation
• Agglomerative Clustering
• DBSCAN
• Expectation Maximization Clustering
• Extract Cluster Prototypes
• Flatten Clustering
• Random Clustering
• Support Vector Clustering
• Top Down Clustering
• X-Means
• k-Means
• k-Means (H2O)
• k-Means (Kernel)
• k-Means (fast)
• k-Medoids
• Associations
• Apply Association Rules
• Create Association Rules
• FP-Growth
• Generalized Sequential Patterns
• Item Sets to Data
• Unify Item Sets
• Correlations
• ANOVA Matrix
• Correlation Matrix
• Covariance Matrix
• Grouped ANOVA
• Mutual Information Matrix
• Rainflow Matrix
• Transition Graph
• Transition Matrix
• Similarities
• Cross Distances
• Data to Similarity
• Data to Similarity Data
• Similarity to Data
• Feature Weights
• Data to Weights
• Weight by Chi Squared Statistic
• Weight by Component Model
• Weight by Correlation
• Weight by Deviation
• Weight by Gini Index
• Weight by Information Gain
• Weight by Information Gain Ratio
• Weight by PCA
• Weight by Relief
• Weight by Rule
• Weight by SVM
• Weight by Tree Importance
• Weight by Uncertainty
• Weight by User Specification
• Weight by Value Average
• Weights to Data
• Optimization
• Parameters
• Clone Parameters
• Optimize Parameters (Evolutionary)
• Optimize Parameters (Grid)
• Optimize Parameters (Quadratic)
• Set Parameters
• Feature Selection
• Backward Elimination
• Forward Selection
• Optimize Selection
• Optimize Selection (Brute Force)
• Optimize Selection (Evolutionary)
• Optimize Selection (Weight-Guided)
• Feature Generation
• Optimize by Generation (AGA)
• Optimize by Generation (Evolutionary Aggregation)
• Optimize by Generation (GGA)
• Optimize by Generation (YAGGA)
• Optimize by Generation (YAGGA2)
• Feature Weighting
• Optimize Weights (Backward)
• Optimize Weights (Evolutionary)
• Optimize Weights (Forward)
• Optimize Weights (PSO)
• Time Series
• Transformation
• Autocorrelation / Autocovariance
• Differentiate
• Equalize Numerical Indices
• Equalize Time Stamps
• Exponential Smoothing
• Fast Fourier Transformation
• Highest Peak Transformation
• Integrate
• Lag
• Logarithm
• Moving Average Filter
• Normalize (Series)
• Replace Missing Values (Series)
• Z-Score Peak Transformation
• Decomposition
• Classic Decomposition
• STL Decomposition
• Feature Extraction
• Extract Aggregates
• Extract Coefficients (Polynomial Fit)
• Extract Mode
• Extract Peaks
• Windowing
• Process Windows
• Windowing
• Forecasting
• ARIMA
• Apply Forecast
• Default Forecast
• Function and Seasonal Component Forecast
• Holt-Winters
• Multi Horizon Forecast
• Validation
• Forecast Validation
• Multi Horizon Performance
• Sliding Window Validation
• Utility
• Generate Data (ARIMA)
• Scoring
• Apply Model
• Confidences
• Apply Threshold
• Create Threshold
• Drop Uncertain Predictions
• Find Threshold
• Generate Prediction
• Generate Prediction Ranking
• Rescale Confidences
• Select Recall
• Validation
• Bootstrapping Validation
• Cross Validation
• Split Validation
• Wrapper Split Validation
• Wrapper-X-Validation
• Performance
• Combine Performances
• Extract Performance
• Multi Label Performance
• Performance
• Performance (Min-Max)
• Performance (User-Based)
• Performance to Data
• Predictive
• Performance (Attribute Count)
• Performance (Binominal Classification)
• Performance (Classification)
• Performance (Costs)
• Performance (Ranking)
• Performance (Regression)
• Performance (Support Vector Count)
• Segmentation
• Cluster Count Performance
• Cluster Density Performance
• Cluster Distance Performance
• Item Distribution Performance
• Map Clustering on Labels
• Significance Tests
• ANOVA
• T-Test
• Visual
• Compare ROCs
• Create Lift Chart
• Visualize Model by SOM
• Utility
• Execute Process
• Multiply
• Subprocess
• Scripting
• Execute Program
• Execute Python
• Execute R
• Execute SQL
• Execute Script
• Process Control
• Publish to App
• Recall
• Recall from App
• Remember
• Loops
• Loop
• Loop Attribute Subsets
• Loop Attributes
• Loop Batches
• Loop Clusters
• Loop Collection
• Loop Data Fractions
• Loop Data Sets
• Loop Examples
• Loop Files
• Loop Labels
• Loop Parameters
• Loop Repository
• Loop Until
• Loop Values
• Loop Zip-File Entries
• Loop and Average
• Loop and Deliver Best
• Branches
• Branch
• Select Subprocess
• Collections
• Average
• Collect
• Flatten Collection
• Select
• Exceptions
• Handle Exception
• Throw Exception
• Macros
• Extract Macro
• Generate Macro
• Set Macro
• Set Macros
• Unset Macro
• Files
• Add Entry to Archive File
• Copy File
• Create Archive File
• Create Directory
• Delete File
• Move File
• Open File
• Rename File
• Write File
• Write Message
• Write as Text
• Annotations
• Annotate
• Annotations to Data
• Data to Annotations
• Extract Macro from Annotation
• Logging
• Clear Log
• Extract Log Value
• Log
• Log to Data
• Log to Weights
• Print to Console
• Provide Macro as Log Value
• Data Anonymization
• De-Obfuscate
• Obfuscate
• Random Data Generation
• Add Noise
• Create ExampleSet
• Generate Churn Data
• Generate Data
• Generate Direct Mailing Data
• Generate Massive Data
• Generate Multi-Label Data
• Generate Nominal Data
• Generate Sales Data
• Generate Team Profit Data
• Generate Transaction Data
• Generate Transfer Data
• Generate Up-Selling Data
• Misc
• Delay
• Free Memory
• Join Paths
• Materialize Data
• Send Mail
• Deployment
• Remote Python Context