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bdpedigo/
local_compartment_classifier_bd_boxes

Name: local_compartment_classifier_bd_boxes
Availability: InStock

sklearn

skops

tabular-classification

mit

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Model description

This is a model trained to classify pieces of neuron as axon, dendrite, soma, or glia, based only on their local shape and synapse features.The model is a linear discriminant classifier which was trained on compartment labels generated by Bethanny Danskin for 3 6x6x6 um boxes in the Minnie65 Phase3 dataset.

Intended uses & limitations

This model could be used to predict some compartment labels in mouse cortical connectomes, but it is unclear to what extent this model will generalize.

Training Procedure

The model was trained on local (level 2 cache) and synapse count features from 3 6x6x6 um boxes in the Minnie65 Phase3 dataset. These features were also locally aggregated in 5-hop neighborhood windows and concatenated to each level 2 node's features. The labels were generated by Bethanny Danskin and include axon, dendrite, soma, and glia compartments. The classification model was trained using a linear discriminant classifier.

Hyperparameters

Click to expand

Hyperparameter	Value
memory
steps	[('transformer', QuantileTransformer(output_distribution='normal')), ('lda', LinearDiscriminantAnalysis(n_components=3))]
verbose	False
transformer	QuantileTransformer(output_distribution='normal')
lda	LinearDiscriminantAnalysis(n_components=3)
transformer__copy	True
transformer__ignore_implicit_zeros	False
transformer__n_quantiles	1000
transformer__output_distribution	normal
transformer__random_state
transformer__subsample	10000
lda__covariance_estimator
lda__n_components	3
lda__priors
lda__shrinkage
lda__solver	svd
lda__store_covariance	False
lda__tol	0.0001

Model Plot

Pipeline(steps=[('transformer',QuantileTransformer(output_distribution='normal')),('lda', LinearDiscriminantAnalysis(n_components=3))])

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Evaluation Results

Classification Report (overall)

type	precision	recall	f1-score	support
accuracy	0.944357	0.944357	0.944357	0.944357
macro avg	0.854825	0.917289	0.878753	31307
weighted avg	0.946879	0.944357	0.945155	31307

Classification Report (by class)

class	precision	recall	f1-score	support
axon	0.956309	0.964704	0.960488	16404
dendrite	0.928038	0.911341	0.919614	6948
glia	0.964442	0.935279	0.949636	7540
soma	0.570513	0.857831	0.685274	415

How to Get Started with the Model

[More Information Needed]

Model Card Authors

Ben Pedigo Bethanny Danskin

bdpedigo/local_compartment_classifier_bd_boxes