Figure 7

Predictive modeling using Mito Hacker-generated data. (a) The decision structure behind the classification of the three different cell lines. The structure suggests that the average of the area of the mitochondria across the cells is a strong predictor of the cell line. (b) List of the important features in distinguishing the morphological structures among different cell lines, ranked based on the achieved information gain after splitting the data. This is the ranking of the features after removing the highly correlated features from the dataset, using the IVF method. (c) The confusion matrix of the model after outlier removal. The matrix shows that the majority of the drop in the performance happens because the model is not able to effectively separate KPDC253 and KPDC143 (~ %75 accuracy). (d) Three representative cells from each of the three different cell lines demonstrating the apparent morphological similarity between KDPC253 and KPDC143. Scale Bars: 10 μm.