Comments (5)
Yeah, probably, though for this ticket I was thinking to just extract the variance
from deeplens-experiments.
There is no variance in precision, f1-score or recall within a species for multiple runs using kmeans.
This table shows there is only one value for each metric per species across 8 runs: http://165.227.103.185:5601/app/kibana#/visualize/edit/de1a88d0-680b-11e8-aa7a-89fb74d43a0e?_g=()&_a=(filters:!(),linked:!t,query:(language:lucene,query:''),uiState:(vis:(params:(sort:(columnIndex:3,direction:desc)))),vis:(aggs:!((enabled:!t,id:'1',params:(),schema:metric,type:count),(enabled:!t,id:'2',params:(field:label.keyword,size:100),schema:bucket,type:significant_terms),(enabled:!t,id:'9',params:(field:f1-score),schema:metric,type:cardinality),(enabled:!t,id:'10',params:(field:precision),schema:metric,type:cardinality),(enabled:!t,id:'11',params:(field:recall),schema:metric,type:cardinality)),params:(perPage:100,showMeticsAtAllLevels:!f,showPartialRows:!f,showTotal:!f,sort:(columnIndex:3,direction:desc),totalFunc:sum),title:'k-means+accuracy+variance',type:table))
from deeplens-experiments.
Oh, interesting. Is there a way to put error bars on the charts?
https://www.elastic.co/guide/en/elasticsearch/guide/current/_building_bar_charts.html
from deeplens-experiments.
There is a random seed that I might need to change to be actually random too
from deeplens-experiments.
Added a runid
from deeplens-experiments.
Related Issues (20)
- Build yolo docker image #11 failed HOT 1
- What is the affect of the "neighbors" parameters on the performance of k-means? HOT 2
- Extract Hyperparameters to Splunk Fields HOT 2
- Experiments need to track "power" of the result
- Build an ELK stack, expose to accept incoming data HOT 11
- How does image size correlate to accuracy with k-means?
- Set up a file format for an "experiment" that the protocol for the experiment
- Set up a file format to determine "success" for an experiment
- Write a script to capture experiment results, i.e. data + screenshots of charts
- Models need to be saved off when experiment completes HOT 1
- Take a screenshot of chart from a completed experiment, upload screenshot to github
- Check experiments into git HOT 1
- Write some sort of automated tests that can verify experiments are written correctly HOT 1
- Change docker image running to execute the containers on AWS instead of a local jenkins
- If a container runs on AWS, add a dollar cost estimate to the data saved in elasticsearch HOT 1
- Number of issues processed should be saved off for reporting
- Screen to track model performance over time
- Isolate python installation used for training/testing
- Build yolo docker image #9 failed HOT 1
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from deeplens-experiments.