Imputation (imputation)

Imputation replaces missing feature values with appropriate values. The example below shows how to replace the missing values with variables’ averages:

import Orange
bridges = Orange.data.Table("bridges")
imputed_bridges = Orange.data.imputation.ImputeTable(bridges,
    method=Orange.feature.imputation.AverageConstructor())

print "Original data set:"
for e in bridges[:3]:
    print e

print "Imputed data set:"
for e in imputed_bridges[:3]:
    print e

The output of this code is:

Original data set:
['M', 1818, 'HIGHWAY', ?, 2, 'N', 'THROUGH', 'WOOD', 'SHORT', 'S', 'WOOD']
['A', 1819, 'HIGHWAY', 1037, 2, 'N', 'THROUGH', 'WOOD', 'SHORT', 'S', 'WOOD']
['A', 1829, 'AQUEDUCT', ?, 1, 'N', 'THROUGH', 'WOOD', '?', 'S', 'WOOD']

Imputed data set:
['M', 1818, 'HIGHWAY', 1300, 2, 'N', 'THROUGH', 'WOOD', 'SHORT', 'S', 'WOOD']
['A', 1819, 'HIGHWAY', 1037, 2, 'N', 'THROUGH', 'WOOD', 'SHORT', 'S', 'WOOD']
['A', 1829, 'AQUEDUCT', 1300, 1, 'N', 'THROUGH', 'WOOD', 'MEDIUM', 'S', 'WOOD']

The function uses feature imputation methods from Imputation (imputation) and applies them on entire data set. The supported methods are: