Orange Widgets

Orange widgets are building blocks of data analysis workflows that are assembled in Orange’s visual programming environment.

Widgets are grouped into classes according to their function. A typical workflow may mix widgets for data input and filtering, visualization, and predictive data mining.

Data

File	Paint Data	Data Table
Select Attributes	Rank	Purge Domain
Merge Data	Concatenate	Data Sampler
Select Data	Save	Discretize
Continuize	Impute	Outliers
Edit Domain	Python Script

Visualize

Distributions	Scatter Plot	Attribute Statistics
Linear Projection	Radviz	Polyviz
Parallel Coordinates	Survey Plot	Mosaic Display
Sieve Diagram	Sieve Multigram

Classify

Naive Bayesian Learner	SVM Learner	Logistic Regression Learner
Majority Learner	Classification Tree Learner	Classification Tree Graph
Classification Tree Viewer	CN2 Rule Learner	Rule Viewer
k-Nearest Neighbours Learner	Nomogram	Random Forest
C4.5 Learner	Interactive Tree Builder

Regression

Mean Learner	Linear Regression Learner	Regression Tree Learner
Regression Tree Viewer	Pade

Evaluate

Confusion Matrix	ROC Analysis	Lift Curve
Calibration Plot	Test Learners	Predictions

Associate

Association Rules	Association Rules Filter	Association Rules Tree Viewer
Item Sets	Item Sets Explorer

Unsupervised

Distance File	Save Distance File	Matrix Transformation
Distance Matrix Filter	Distance Map	Example Distance
Attribute Distance	Hierarchical Clustering	Interaction Graph
K-Means Clustering	MDS	Principal Component Analysis
SOM	SOM Visualizer

Index:

• File
• Paint Data
• Data Table
• Select Attributes
• Rank
• Purge Domain
• Merge Data
• Concatenate
• Data Sampler
• Select Data
• Save
• Discretize
• Continuize
• Impute
• Outliers
• Edit Domain
• Python Script
• Distributions
• Scatter Plot
• Attribute Statistics
• Linear Projection
• Radviz
• Polyviz
• Parallel Coordinates
• Survey Plot
• Mosaic Display
• Sieve Diagram
• Naive Bayesian Learner
• SVM Learner
• Logistic Regression Learner
• Majority Learner
• Classification Tree Learner
• Classification Tree Graph
• Classification Tree Viewer
• CN2 Rule Learner
• Rule Viewer
• k-Nearest Neighbours Learner
• Nomogram
• Random Forest
• C4.5 Learner
• Interactive Tree Builder
• Mean Learner
• Linear Regression Learner
• Regression Tree Learner
• Regression Tree Viewer
• Pade
• Confusion Matrix
• ROC Analysis
• Lift Curve
• Calibration Plot
• Test Learners
• Predictions
• Association Rules
• Association Rules Filter
• Association Rules Tree Viewer
• Distance File
• Distance Map
• Example Distance
• Attribute Distance
• Hierarchical Clustering
• Interaction Graph
• K-Means Clustering
• MDS
• Principal Component Analysis

Index and search

• Index
• Search Page