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I was wondering if we could collaborate on a library for specifically for evaluation metrics in Machine Learning. In the confuse library, we currently have implemented the following binary and multi-class evaluation metrics.
Counts
True positives
False positives
False negatives
True negatives
Binary class Metrics
sensitivity / specificity / true positive rate
specificity / true negative rate
false positive rate
false negative rate
precision
f1-score
accuracy
misclassification-rate
confusion matrix
Multi-class metrics
Micro averaged fmeasure/precision/recall
Macro averaged fmeasure/precision/recall
I observed that cortex implements metrics in a different name space too.
If the idea of moving all evaluation metrics to a separate library is acceptable, we could help migrate & test Cortex code that uses these metric APIs.
I believe it will be helpful for the larger Clojure data science community as there is currently no Clojure library (to my knowledge) that provides these APIs.
Would you like to hear what do you folks think about this.
regards
Kiran
The text was updated successfully, but these errors were encountered:
This sounds reasonable. We are about to include a solid chunk of metrics that involve bounding boxes of things which could be a nice addition to the library you are talking about.
Hi all,
How are you doing?
I was wondering if we could collaborate on a library for specifically for evaluation metrics in Machine Learning. In the confuse library, we currently have implemented the following binary and multi-class evaluation metrics.
Counts
Binary class Metrics
Multi-class metrics
I observed that cortex implements metrics in a different name space too.
If the idea of moving all evaluation metrics to a separate library is acceptable, we could help migrate & test Cortex code that uses these metric APIs.
I believe it will be helpful for the larger Clojure data science community as there is currently no Clojure library (to my knowledge) that provides these APIs.
Would you like to hear what do you folks think about this.
regards
Kiran
The text was updated successfully, but these errors were encountered: