Orange Visual Programming

Getting Started

Here we need to copy the getting started guide.

• Loading your Data
• Building Workflows
• Exporting Models
• Exporting Visualizations
• Learners as Scorers
• Report

Widgets

Data

• File
• CSV File Import
• Datasets
• SQL Table
• Save Data
• Data Info
• Aggregate Columns
• Data Table
• Select Columns
• Select Rows
• Data Sampler
• Transpose
• Discretize
• Continuize
• Create Instance
• Create Class
• Randomize
• Concatenate
• Select by Data Index
• Paint Data
• Pivot Table
• Python Script
• Feature Constructor
• Edit Domain
• Impute
• Merge Data
• Outliers
• Preprocess
• Apply Domain
• Purge Domain
• Rank
• Correlations
• Color
• Feature Statistics
• Melt
• Neighbors
• Unique
• Group by

Visualize

• Box Plot
• Violin Plot
• Distributions
• Heat Map
• Scatter Plot
• Line Plot
• Bar Plot
• Venn Diagram
• Linear Projection
• Sieve Diagram
• Pythagorean Tree
• Pythagorean Forest
• CN2 Rule Viewer
• Mosaic Display
• Silhouette Plot
• Tree Viewer
• Nomogram
• FreeViz
• Radviz

Model

• Constant
• CN2 Rule Induction
• Calibrated Learner
• kNN
• Tree
• Random Forest
• Gradient Boosting
• SVM
• Linear Regression
• Logistic Regression
• Naive Bayes
• AdaBoost
• Curve Fit
• Neural Network
• Stochastic Gradient Descent
• Stacking
• Load Model
• Save Model

Evaluate

• Calibration Plot
• Confusion Matrix
• Performance Curve
• Predictions
• ROC Analysis
• Test and Score

Unsupervised

• PCA
• Correspondence Analysis
• Distance Map
• Distances
• Distance Matrix
• Distance Transformation
• Distance File
• Save Distance Matrix
• Hierarchical Clustering
• k-Means
• Louvain Clustering
• DBSCAN
• MDS
• Example
• References
• t-SNE
• Manifold Learning
• Self-Organizing Map