Index

_

__init__() (pyCellPhenoX.CellPhenoX method)

B

balanced_sample() (in module pyCellPhenoX.utils.balanced_sample)

C

CellPhenoX (class in pyCellPhenoX)

check_indices() (in module pyCellPhenoX.utils.check_indices)

G

get_best_model() (pyCellPhenoX.CellPhenoX method) get_best_score() (pyCellPhenoX.CellPhenoX method) get_interpretable_score() (pyCellPhenoX.CellPhenoX method) get_model_training_time() (pyCellPhenoX.CellPhenoX method)

get_prc_curves() (pyCellPhenoX.CellPhenoX method) get_roc_curves() (pyCellPhenoX.CellPhenoX method) get_shap_values() (pyCellPhenoX.CellPhenoX method) get_shap_values_per_cv() (pyCellPhenoX.CellPhenoX method)

M

marker_discovery() (in module pyCellPhenoX.marker_discovery) model_training_shap_val() (pyCellPhenoX.CellPhenoX method) module pyCellPhenoX.marker_discovery pyCellPhenoX.nonnegativeMatrixFactorization pyCellPhenoX.preprocessing pyCellPhenoX.principalComponentAnalysis pyCellPhenoX.utils.balanced_sample pyCellPhenoX.utils.check_indices pyCellPhenoX.utils.reducedim pyCellPhenoX.utils.select_num_components pyCellPhenoX.utils.select_optimal_k

N

nonnegativeMatrixFactorization() (in module pyCellPhenoX.nonnegativeMatrixFactorization)

P

preprocessing() (in module pyCellPhenoX.preprocessing) principalComponentAnalysis() (in module pyCellPhenoX.principalComponentAnalysis) pyCellPhenoX.marker_discovery module pyCellPhenoX.nonnegativeMatrixFactorization module pyCellPhenoX.preprocessing module pyCellPhenoX.principalComponentAnalysis module

pyCellPhenoX.utils.balanced_sample module pyCellPhenoX.utils.check_indices module pyCellPhenoX.utils.reducedim module pyCellPhenoX.utils.select_num_components module pyCellPhenoX.utils.select_optimal_k module

R

reduceDim() (in module pyCellPhenoX.utils.reducedim)

S

select_number_of_components() (in module pyCellPhenoX.utils.select_num_components) select_optimal_k() (in module pyCellPhenoX.utils.select_optimal_k)

shap_values_explainer() (pyCellPhenoX.CellPhenoX method) split_data() (pyCellPhenoX.CellPhenoX method)