| |
Methods defined here:
- __init__(self, object=None, object_order_column=None)
- DESCRIPTION:
The ScaleSummary function takes as input ScaleMap output (statistics
assembled at the vworker level) and outputs global statistical
information for the entire input data set.
PARAMETERS:
object:
Required Argument.
Specifies the teradataml DataFrame containing statistic input
generated by ScaleMap or instance of ScaleMap.
object_order_column:
Optional Argument.
Specifies Order By columns for data.
Values to this argument can be provided as a list, if multiple
columns are used for ordering.
Types: str OR list of Strings (str)
RETURNS:
Instance of ScaleSummary.
Output teradataml DataFrames can be accessed using attribute
references, such as ScaleSummaryObj.<attribute_name>.
Output teradataml DataFrame attribute name is:
result
RAISES:
TeradataMlException
EXAMPLES:
# Load example data.
# The table 'scale_housing' contains house properties
# like the number of bedrooms, lot size, the number of bathrooms, number of stories etc.
# The table 'scale_stat' is the statistic data(genererated by ScaleMap function) of the scale_housing data.
load_example_data("scale", "scale_stat")
load_example_data("scalemap", "scale_housing")
# Create teradataml DataFrame objects.
scale_stat_input = DataFrame.from_table("scale_stat")
scale_housing = DataFrame.from_table("scale_housing")
# Example 1 - This functions takes the input as ScaleMap output (scale_stat)
# and outputs global statistical information for the entire input data set.
scale_summary_out = ScaleSummary(object=scale_stat_input)
# Print the result DataFrame
print(scale_summary_out)
# Example 2 - This example scales (normalizes) input data using the
# midrange method and the default values for the arguments Intercept
# and Multiplier (0 and 1, respectively).
scale_map_out = ScaleMap(data = scale_housing,
input_columns = ['price','lotsize','bedrooms','bathrms','stories']
)
scale_summary_out = ScaleSummary(object=scale_map_out)
# Print the result DataFrame
print(scale_summary_out)
- __repr__(self)
- Returns the string representation for a ScaleSummary class instance.
- get_build_time(self)
- Function to return the build time of the algorithm in seconds.
When model object is created using retrieve_model(), then the value returned is
as saved in the Model Catalog.
- get_prediction_type(self)
- Function to return the Prediction type of the algorithm.
When model object is created using retrieve_model(), then the value returned is
as saved in the Model Catalog.
- get_target_column(self)
- Function to return the Target Column of the algorithm.
When model object is created using retrieve_model(), then the value returned is
as saved in the Model Catalog.
- show_query(self)
- Function to return the underlying SQL query.
When model object is created using retrieve_model(), then None is returned.
|