extract_feature_expression: Internal function to extract feature expressions.

In familiar: End-to-End Automated Machine Learning and Model Evaluation

Internal function to extract feature expressions.

Description

Computes and extracts feature expressions for features used in a familiarEnsemble object.

Usage

extract_feature_expression(
  object,
  data,
  feature_similarity,
  sample_similarity,
  feature_cluster_method = waiver(),
  feature_linkage_method = waiver(),
  feature_similarity_metric = waiver(),
  sample_cluster_method = waiver(),
  sample_linkage_method = waiver(),
  sample_similarity_metric = waiver(),
  evaluation_times = waiver(),
  message_indent = 0L,
  verbose = FALSE,
  ...
)

Arguments

object	A familiarEnsemble object, which is an ensemble of one or more familiarModel objects.
data	A dataObject object, data.table or data.frame that constitutes the data that are assessed.
feature_similarity	Table containing pairwise distance between sample. This is used to determine cluster information, and indicate which samples are similar. The table is created by the extract_sample_similarity method.
feature_cluster_method	The method used to perform clustering. These are the same methods as for the cluster_method configuration parameter: none, hclust, agnes, diana and pam. none cannot be used when extracting data regarding mutual correlation or feature expressions. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
feature_linkage_method	The method used for agglomerative clustering in hclust and agnes. These are the same methods as for the cluster_linkage_method configuration parameter: average, single, complete, weighted, and ward. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
feature_similarity_metric	Metric to determine pairwise similarity between features. Similarity is computed in the same manner as for clustering, and feature_similarity_metric therefore has the same options as cluster_similarity_metric: mcfadden_r2, cox_snell_r2, nagelkerke_r2, spearman, kendall and pearson. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
sample_cluster_method	The method used to perform clustering based on distance between samples. These are the same methods as for the cluster_method configuration parameter: hclust, agnes, diana and pam. none cannot be used when extracting data for feature expressions. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
sample_linkage_method	The method used for agglomerative clustering in hclust and agnes. These are the same methods as for the cluster_linkage_method configuration parameter: average, single, complete, weighted, and ward. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
sample_similarity_metric	Metric to determine pairwise similarity between samples. Similarity is computed in the same manner as for clustering, but sample_similarity_metric has different options that are better suited to computing distance between samples instead of between features: gower, euclidean. The underlying feature data is scaled to the [0, 1] range (for numerical features) using the feature values across the samples. The normalisation parameters required can optionally be computed from feature data with the outer 5% (on both sides) of feature values trimmed or winsorised. To do so append ⁠_trim⁠ (trimming) or ⁠_winsor⁠ (winsorising) to the metric name. This reduces the effect of outliers somewhat. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects.
evaluation_times	One or more time points that are used for in analysis of survival problems when data has to be assessed at a set time, e.g. calibration. If not provided explicitly, this parameter is read from settings used at creation of the underlying familiarModel objects. Only used for survival outcomes.
message_indent	Number of indentation steps for messages shown during computation and extraction of various data elements.
verbose	Flag to indicate whether feedback should be provided on the computation and extraction of various data elements.
...	Unused arguments.

Value

A list with a data.table containing feature expressions.

familiar documentation built on Sept. 30, 2024, 9:18 a.m.