cblearn.embedding.DimensionEstimationResult

class cblearn.embedding.DimensionEstimationResult(estimated_dimension, dimensions, train_scores, test_scores, stats_result)

Result object for dimensionality estimation of embeddings.

estimated_dimension

The estimated dimensionality

Type:

int

dimensions

The tested dimensions

Type:

numpy.ndarray

train_scores

The training scores for each dimension

Type:

numpy.ndarray

test_scores

The test scores for each dimension

Type:

numpy.ndarray

stats_result

The result of the hypothesis test

Type:

dict

__init__(estimated_dimension, dimensions, train_scores, test_scores, stats_result)

Methods

__init__(estimated_dimension, dimensions, ...)
plot_scores([train_kwargs, test_kwargs])	Plot the train and test scores per dimesionality of the embedding.

Attributes

estimated_dimension
dimensions
train_scores
test_scores
stats_result

plot_scores(train_kwargs={}, test_kwargs={})

Plot the train and test scores per dimesionality of the embedding.

Parameters:

• train_kwargs – Keyword arguments for the training scores plot.

• test_kwargs – Keyword arguments for the test scores plot.