API

• Feature engineer
• Feature selection
• Metrics

Overview of feature engineer API

operation	description
count	count the occurrences of some categorical features within dataset.
cumsum	the calculation of the cumulative sum.
denoising autoencoder	train a denoising autoencoder neural network for feature extraction. reference
dimension reduction	use dimension reduction technology for feature extraction, such as Principal Component Analysis (PCA).
gbdt	Generating Features with Gradient Boosted Decision Trees. reference
rank	Compute numerical data ranks.
rolling	statistics calculation within rolling windows.
shift	lag feature.
diff	first Difference.
statistics	statistics calculation.
time parse feature	parse time feature for time column, such as year, month, day, hour, dayofweek, and so on.
cross feature	synthetic feature formed by multiplying (crossing) two or more features. reference

Overview of feature selection API

operation	description
Adversarial Validation	a feature selection solution for battling overfitting. reference
GRN	a feature selection using Gated Residual Networks (GRN) and Variable Selection Networks (VSN). reference

Overview of Metrics API

operation	description
MAE	mean absolute error
MAPE	mean absolute percentage error
MSE	mean squared error
MSLE	mean squared logarithmic error
RMSLE	root mean squared logarithmic error