Load and edit your data in the File widget.

Paint a two-dimensional data set.

Data selection in Scatter Plot is visualised in a Box Plot.

Orange can suggest which widget to add to the workflow.

Join two data sets.

Box plot displays basic statistics of attributes.

Sieve diagram on titanic data set.

Heatmap visualisation

Explorative analysis of Pythagorean classification trees.

View image files in the data set.

Hierarchial clustering of data instances.

Playing with Paint Data and an automatic selection of clusters in k-Means.

Multidimensional scaling plots data with many features into a 2D space.

Principal component analysis.

Receiver operating characteristics (ROC) analysis.

Cross-validated calibration plot

Data preprocessing turned into component of a learning algorithm

Feature scoring for finding interesting visualizations.

Model-based feature scoring.

Cross-validation and scoring of classifiers.

Visualizing misclassifications.

Finding joint misclassifications of three models.

Construct a model on train data and test with test data.

Comparing low silhouette scores and misclassifications.

CN2 rule induction.

Visualizing Polynomial Regression.

Interactive gradient descent.

Predicting text categories.

Topic modelling of recent tweets.

Image embedding with ImageNet neural network.