Nyoka

Major Changes
* Removed customized elements from PMML schema. Now, Nyoka is completely [Official PMML 4.4.1](http://dmg.org/pmml/v4-4-1/GeneralStructure.html) schema compliant.
* Dropped support for Keras and Retinanet exporter as these two exporters were using customized DeepNetwork element.

CICD
* Usage of `Travis-CI` is discontinued. Instead of that `Github Actions` is used

Minor Update
* Added support for PMML schema 4.4.1

Minor update
* Added support for the latest version of scikit-learn (<=0.23.1)

Bug fix
* Removed Python version constraint from `setup.py`. Now user can install nyoka when python version is >= 3.6

Added exporter for TrendMiner's fingerprint
* This can be imported as `from nyoka.custom.trendminer import FingerprintToPmml`

Minor Update
* Added support for `VARMAX` from statsmodels library (multi-variate time series model)
* `ArimaToPMML` is deprecated and `StatsmodelsToPmml` is introduced
* `conf_int` parameter is added to StatsmodelsToPmml which will generate OutputField for lower and upper bound of confidence interval
* Added support for ARIMA in state space form from statsmodels library.

Structural change
* Added `nyoka.base.enums.py` which contains enum for all enumerations present in PMML schema
* Added example jupyter notebook for VARMAX

Schema update
* Added `InterceptVector`, `PredictedStateCovarianceMatrix` and `SelectedStateCovarianceMatrix` as child element and `observationVariance` as attribute of StateSpaceModel element
* Two new result-feature `confidenceIntervalUpper` and `confidenceIntervalLower` are added to schema

Minor Update
* `model_name` and `description` parameters are added to all the exporters.
* Updated PMML schema for KalmanState element
* Updated Arima exporter to export outputfield for predictionInterval with feature type "standardError"
Bug fixes
* Now the endog for ARIMA/SARIMAX can be any iterable
* Timestamp value in Header is updated from `utcnow()` to `now()`