psych_kxi_ensemble_models {opticskxi} | R Documentation |
Example pipeline for ensemble models
Description
Example pipeline for ensemble models on mental health related natural language processing
Usage
psych_kxi_ensemble_models(
m_data,
...,
n_models = 4,
metrics = NULL,
metrics_exclude = NULL,
model_subsample = c(0.1, 0.2, 0.5),
n_models_subsample = 10
)
Arguments
m_data |
Data matrix Data frame returned by optics |
... |
Passed to function psych_kxi_pipeline |
n_models |
Number of best models to return |
metrics |
Names of metrics to use. Any of those computed by opticskxi_pipeline, e.g. 'sindex', 'ch', 'dunn', 'dunn2', 'widestgap', 'entropy' etc. NULL for all (8). |
metrics_exclude |
Names of metrics to exclude. Typically used with metrics = NULL. E.g. 'entropy'. |
model_subsample |
Ratios of best models to consider. |
n_models_subsample |
Number of best models when subsampling. |
Value
Input parameter data frame with with results binded in columns optics, clusters and metrics. Subsetted to best models according to ensemble metrics.
Examples
data('m_psychwords')
m_psychwords = m_psychwords[1:200, 1:20]
df_params = expand.grid(n_xi = 4:5, pts = c(5, 10), dist = 'cosine',
dim_red = 'ICA', n_dimred_comp = 5)
df_kxi = psych_kxi_ensemble_models(m_psychwords, df_params,
n_min_clusters = 2,
n_models = 4,
metrics = c('avg.silwidth', 'dunn'),
model_subsample = c(0.4, 0.6),
n_models_subsample = 4)
[Package opticskxi version 1.1.0 Index]