An identifier for the model. User in score and error reporting.
feature names (parallel to featureFunctions)
feature extracting functions.
representation of the regression model parameters.
a function applied to the inner product of the input vector and weight vector.
an optional calibration spline to Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers, Zadrozny, Elkan (ICML, 2001). This is applied prior to invLinkFunction
if provided, we check whether the threshold is exceeded. If so, return an error instead of the computed score. This is for missing data situations.
Container for information returned by RegressionFeatures.constructFeatures.
representation of the regression model parameters.
Extract the features from the raw data by mapping featureFunctions over the input.
Extract the features from the raw data by mapping featureFunctions over the input. If numMissingThreshold is not None and the number of resulting empty Iterables exceeds the numMissingThreshold value, then the resulting Features.missingOk value is false; otherwise, it will be true. If Features.missingOk is false, then go back and check all feature functions for missing values and add findings to the Features.missing map. This Features.missing is a mapping from the feature specification to the list of variable names whose associated values are missing from the input.
raw input data of the model input type.
a Features instance with the following: 1 the transformed input vector 1 the map of bad features to the missing values in the raw data that were needed to compute the feature 1 whether the amount of missing data is acceptable to still continue
Issue a debug logging message, with an exception.
Issue a debug logging message, with an exception.
the message object. toString() is called to convert it
to a loggable string.
the exception to include with the logged message.
Issue a debug logging message.
Issue a debug logging message.
the message object. toString() is called to convert it
to a loggable string.
Issue a trace logging message, with an exception.
Issue a trace logging message, with an exception.
the message object. toString() is called to convert it
to a loggable string.
the exception to include with the logged message.
Issue a trace logging message.
Issue a trace logging message.
the message object. toString() is called to convert it
to a loggable string.
feature extracting functions.
feature extracting functions.
feature names (parallel to featureFunctions)
feature names (parallel to featureFunctions)
Issue a trace logging message, with an exception.
Issue a trace logging message, with an exception.
the message object. toString() is called to convert it
to a loggable string.
the exception to include with the logged message.
Issue a trace logging message.
Issue a trace logging message.
the message object. toString() is called to convert it
to a loggable string.
a function applied to the inner product of the input vector and weight vector.
Determine whether debug logging is enabled.
Determine whether debug logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Determine whether trace logging is enabled.
Get the Logger for the class that mixes this trait in.
Get the Logger for the class that mixes this trait in. The Logger
is created the first time this method is call. The other methods (e.g.,
error, info, etc.) call this method to get the logger.
the Logger
Get the name associated with this logger.
Get the name associated with this logger.
the name.
An identifier for the model.
An identifier for the model. User in score and error reporting.
if provided, we check whether the threshold is exceeded.
if provided, we check whether the threshold is exceeded. If so, return an error instead of the computed score. This is for missing data situations.
an optional calibration spline to Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers, Zadrozny, Elkan (ICML, 2001).
an optional calibration spline to Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers, Zadrozny, Elkan (ICML, 2001). This is applied prior to invLinkFunction
Get the score.
Issue a trace logging message, with an exception.
Issue a trace logging message, with an exception.
the message object. toString() is called to convert it
to a loggable string.
the exception to include with the logged message.
Issue a trace logging message.
Issue a trace logging message.
the message object. toString() is called to convert it
to a loggable string.
Issue a trace logging message, with an exception.
Issue a trace logging message, with an exception.
the message object. toString() is called to convert it
to a loggable string.
the exception to include with the logged message.
Issue a trace logging message.
Issue a trace logging message.
the message object. toString() is called to convert it
to a loggable string.
A regression model capable of doing not only linear regression but polynomial regression in general.
This is useful because these conversions allow implicit conversion function from some of the AnyVal types and Options of AnyVal types to Iterable[(String, Double)]. This is useful because specifying features in the JSON spec like:
{ ... "features": { "intercept": "-3", "income": "${user.profile.income}" } }into sequences like:
For more information, see com.eharmony.aloha.models.reg.RegressionModelValueToTupleConversions.
model input type
model output type. to convert from B to com.eharmony.aloha.score.Scores.Score
An identifier for the model. User in score and error reporting.
feature names (parallel to featureFunctions)
feature extracting functions.
representation of the regression model parameters.
a function applied to the inner product of the input vector and weight vector.
an optional calibration spline to Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers, Zadrozny, Elkan (ICML, 2001). This is applied prior to invLinkFunction
if provided, we check whether the threshold is exceeded. If so, return an error instead of the computed score. This is for missing data situations.