Table 3.

Influence of features on the prediction of daughter cell type (%)^a

	Morphology at mitosis	Morphology at birth	Cell type	Process stability	Process retraction	Cell cycle	Mitotic plane angle	Trans‐location	Mitosis location
Only feature	62	63.9	49.7	60.3	51.4	50	49.5	51.2	48.3
Without feature	91.4	92.8	98.4	93.5	96.8	98.2	98.6	98.7	97.2

	Features at birth	Morphological features	Proliferative features	All/no features
Only feature	64	80.3	62	98.9
Without feature	86.2	86.7	93.7	38.2

^aFor the nine features used for clustering, the percentage of correct predictions is shown, using mother cell type and a single feature resp. all features except one. For comparison we display the prediction accuracy if only features known at birth (processes and division position), morphological features (processes at birth and at mitosis), proliferative features (cell‐cycle length, mitosis location, mitotic plane angle, cell type), or all or no features are used for prediction. Bold numbers indicate the best, italic numbers the lowest prediction result. Results are for the combined E65 and E78 dataset, using K = 6 clusters of cell types without constraints, averaged over 20 trials with random cluster initializations. All features have similar influence on the prediction accuracy, with values around or over 50%. Morphological features are the best predictors, yielding accuracies over 62%. The combination of features allows for prediction of the daughter cell type with more than 90% accuracy (98.9% if all features are used).