Comments (1)
The parameter w from the paper is the number of coarse quantizer cells to retrieve for a query before reranking. This implementation instead uses the concept of a result "quota" β it will retrieve as many cells as needed to meet a result quota before reranking. If you want to specify a fixed number of cells, you will need to implement this yourself. See the search code for the current quota-based implementation: https://github.com/yahoo/lopq/blob/master/python/lopq/search.py#L101-L125
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Related Issues (17)
- python search ignores fine codes HOT 2
- When I run the program in windows,i have an error HOT 7
- Pip3 support
- The parameters on large dataset HOT 4
- Missing lopq library in sample `spark-submit` call HOT 2
- Got wrong result by using simple python code in sift1m dataset HOT 2
- Problem with importing lopq package on windows HOT 5
- Do you have any plans that support LOPQ on spark?
- HELP! Exception when data.unpersist() HOT 1
- Exception occurred when copy model file to HDFS HOT 1
- Is there any on-going work to support python3?
- does it need add the distance of query to coarse centroid to the final disοΌ
- search new example
- Dynamic index update HOT 3
- No search method in Spark implementation HOT 5
- Help with PCA/Spark docs HOT 5
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