I’m trying to test metrics from the shap library https://github.com/slundberg/shap/blob/master/shap/benchmark/metrics.py I tried calling metrics like this : But am always getting the error : Answer Try instead: Why? Inspecting package’s top level __init__.py you’ll find out the following commented line:
Tag: metrics
How to get iou of single class in keras semantic segmentation?
I am using the Image segmentation guide by fchollet to perform semantic segmentation. I have attempted modifying the guide to suit my dataset by labelling the 8-bit img mask values into 1 and 2 like in the Oxford Pets dataset. (which will be subtracted to 0 and 1 in class OxfordPets(keras.utils.Sequence):) Question is how do I get the IoU metric
Macro VS Micro VS Weighted VS Samples F1 Score
In sklearn.metrics.f1_score, the f1 score has a parameter called “average”. What does macro, micro, weighted, and samples mean? Please elaborate, because in the documentation, it was not explained properly. Or simply answer the following: Why is “samples” best parameter for multilabel classification? Why is micro best for an imbalanced dataset? what’s the difference between weighted and macro? Answer The question