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https://issues.apache.org/jira/browse/MADLIB-1061?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16758517#comment-16758517
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Frank McQuillan commented on MADLIB-1061:
-----------------------------------------
Here is a proposed changes to the knn interface:
{code}
knn( point_source, -- mandatory params
point_column_name,
point_id,
label_column_name,
test_source,
test_column_name,
test_id,
output_table,
-- optional params
k,
output_neighbors,
fn_dist,
weighted_avg,
algorithm,
algorithm_params
)
algorithm (optional)
TEXT, default: 'brute_force'. Name of the algorithm used to
compute the nearest neighbors. Options are 'brute_force' of 'kd_tree'.
algorithm_params (optional)
TEXT, default 'depth=3, leaf_nodes=2` Comma-delimited list
of name-value pairs for the kd-tree algorithm. Specifies the depth
of the kd-tree and the number of leaf nodes to use, at the specified depth,
when searching for nearest neighbors.
{code}
> Additional computation methods for k-NN - kd tree
> -------------------------------------------------
>
> Key: MADLIB-1061
> URL: https://issues.apache.org/jira/browse/MADLIB-1061
> Project: Apache MADlib
> Issue Type: New Feature
> Components: k-NN
> Reporter: Frank McQuillan
> Assignee: Orhan Kislal
> Priority: Major
> Labels: starter
> Fix For: v1.16
>
> Attachments: KNN-chart-data.pdf, KNN-charts.pdf, KNN-raw.pdf,
> KNN-w-KD-tree-leaf-node-only.pdf, Sheet1-KNN-perf-num-features.pdf,
> Sheet2-KNN-tree-construction.pdf, Sheet3-KNN-tree-depth.pdf
>
>
> Follow on to
> https://issues.apache.org/jira/browse/MADLIB-927
> which uses brute force.
> Determine other k-NN algos to implement. From
> http://scikit-learn.org/stable/modules/neighbors.html
> candidates are:
> * K-D Tree
> * Ball Tree
> * Other?
> This JIRA is to implement K-D tree.
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