2.1.0

- Added support for features with zero variance
- Improved performance and less memory usage

2.0.0

- Switched to the procedure described in Blume, 2012 but normalized by
	a feature's stddev and extended to multiple quantiles
- Improved quantile estimation
- Now returning `pandas.DataFrame`s consistently

1.3.0

- allow for a generic model type
- performance improvements
- extend and enhance tests

1.2.0

- made featureimpact Python3 ready

1.1.0

- it is now assumed that predict() does not change its input
- performance improvements
- improved documentation

1.0.3

- better naming for make_averaged_impact()
- a few minor code improvements
- improved documentation

1.0.2

- added numpy.asarray(X) to FeatureImpact._evaluate() to ensure
	safe prediction evaluation
- adjusted README.txt to include an info about possible features

1.0.1

- added URL to setup script
- better documentation

1.0.0

- initial release
