Measure the information loss of reduction using the variance explained

Metrics are functions that tell how much information would be lost for a given reduction in the data. reduce. as_measure() is a helper function to create new metrics to be used in partitioners. partitioners can be created with as_partitioner().

measure_variance_explained() assesses information loss by calculating the variance explained by the first component of a principal components analysis.

measure_variance_explained(.partition_step)

Arguments

.partition_step

a partition_step object

Value

a partition_step object

See also

Other metrics: as_measure(), measure_icc(), measure_min_icc(), measure_min_r2(), measure_std_mutualinfo()