Orange Visual Programming¶

Getting Started¶

Here we need to copy the getting started guide.

  • Loading your Data

Widgets¶

Data¶

  • File
  • SQL Table
  • Save Data
  • Data Info
  • Data Table
  • Select Columns
  • Select Rows
  • Data Sampler
  • Transpose
  • Discretize
  • Continuize
  • Create Class
  • Randomize
  • Concatenate
  • Paint Data
  • Python Script
  • Feature Constructor
  • Edit Domain
  • Image Viewer
  • Impute
  • Merge Data
  • Outliers
  • Preprocess
  • Purge Domain
  • Rank
  • Color

Visualize¶

  • Box Plot
  • Distributions
  • Heat Map
  • Scatter Plot
  • Venn Diagram
  • Linear Projection
  • Scatter Map
  • Sieve Diagram
  • Pythagorean Tree
  • Pythagorean Forest
  • CN2 Rule Viewer
  • Mosaic Display
  • Silhouette Plot
  • Tree Viewer
  • Geo Map
  • Nomogram

Model¶

  • Naive Bayes
  • Logistic Regression
  • Tree
  • kNN
  • Load Model
  • Constant
  • Random Forest
  • Save Model
  • SVM
  • CN2 Rule Induction
  • AdaBoost
  • Stochastic Gradient Descent
  • Linear Regression

Unsupervised¶

  • PCA
  • Correspondence Analysis
  • Distance Map
  • Distances
  • Distance Matrix
  • Distance Transformation
  • Distance File
  • Save Distance Matrix
  • Hierarchical Clustering
  • k-Means
  • MDS
  • Manifold Learning

Evaluation¶

  • Calibration Plot
  • Confusion Matrix
  • Lift Curve
  • Predictions
  • ROC Analysis
  • Test & Score

Table Of Contents

  • Orange Visual Programming
    • Getting Started
    • Widgets
      • Data
      • Visualize
      • Model
      • Unsupervised
      • Evaluation

Related Topics

  • Documentation overview
    • Next: Loading your Data

This Page

  • Show Source

Quick search

©2015, Orange Data Mining. | Powered by Sphinx 1.5.3 & Alabaster 0.7.10 | Page source