| orange.lecture3 | experimental | The aim of this assignment is to read the iris dataset and to perform various visualisations of the data.
Please note that the Parallel Coordinates widget is unstable. |
| orange.lecture4a | experimental | Inducing and visualising a decision tree.
The aim of this assignment is to induce a decision tree from the data and to visualise its contents. |
| orange.lecture4b | experimental | Evaluating and comparing Decision Tree with Random Decision Forest.
The aim of this assignment is to perform a comparative evaluation of two (related) classifiers. |
| orange.lecture5a | experimental | Data fiting (no prediction).
The aim of this assignment is to fit the housing.dat dataset to a polynomial of different degrees. |
| orange.lecture5b | experimental | Nearest neigbour regresion.
The aim of this assignment is to perform a k nearest neigbour regression on selected features of the housing.tab dataset.
Two values of k are compared. |