PrincipalComponentsModel predict

---

predict(self, frame, mean_centered=True, t_squared_index=False, observation_columns=None, c=None, name=None)

[ALPHA] Predict using principal components model.

Parameters:

frame : Frame

Frame whose principal components are to be computed.

mean_centered : bool (default=True)

Option to mean center the columns. Default is true

t_squared_index : bool (default=False)

Indicator for whether the t-square index is to be computed. Default is false.

observation_columns : list (default=None)

List of observation column name(s) to be used for prediction. Default is the list of column name(s) used to train the model.

c : int32 (default=None)

The number of principal components to be predicted. ‘c’ cannot be greater than the count used to train the model. Default is the count used to train the model.

name : unicode (default=None)

The name of the output frame generated by predict.

Returns:

: Frame

A frame with existing columns and following additional columns:

‘c’ additional columns: containing the projections of V on the the frame ‘t_squared_index’: column storing the t-square-index value, if requested

Predicting on a dataframe’s columns using a PrincipalComponents Model.

Examples

See here for examples.