Specify the data to be used for phenotyping.
PhecapData(
data, hu_feature, label, validation,
patient_id = NULL, subject_weight = NULL,
seed = 12300L, feature_transformation = log1p)A data.frame consisting of all the variables needed for phenotyping, or a character scalar of the path to the data, or a list consisting of either character scalar or data.frame. If a list is given, patient_id cannot be NULL. All the datasets in the list will be joined into a single dataset according to the columns specified by patient_id.
A character scalar or vector specifying the names of one of more healthcare utilization (HU) variables. There variables are always included in the phenotyping model.
A character scalar of the column name that gives the phenotype status (1 or TRUE: present, 0 or FALSE: absent). If label is not ready yet, just put a column filled with NA in data. In such cases only the feature extraction step can be done.
A character scalar, a real number strictly between 0 and 1, or an integer not less than 2. If a character scalar is used, it is treated as the column name in the data that specifies whether this observation belongs to the validation samples (1 or TRUE: validation, 0 or FALSE: training). If a real number strictly between 0 and 1 is used, it is treated as the proportion of the validation samples. The actual validation samples will be drawn from all labeled samples. If an integer not less than 2 is used, it is treated as the size of the validation samples. The actual validation samples will be drawn from all labeled samples.
A character vector for the column names, if any, that uniquely identifies each patient. Such variables must appear in the data. patient_id can be NULL if such fields are not contained in the data.
An optional numeric vector of weights for observations.
If validation samples need to be drawn from all labeled samples, seed specifies the random seed for sampling.
A function that will be applied to all the features.
Since count data are typically right-skewed,
by default log1p will be used.
feature_transformation can be NULL, in which case
no transformation will be done on any of the feature.
An object of class PhecapData.
See PheCAP-package for code examples.