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Diffstat (limited to 'Fundamentals_of_Accelerated_Data_Science/3-05_knn.md')
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diff --git a/Fundamentals_of_Accelerated_Data_Science/3-05_knn.md b/Fundamentals_of_Accelerated_Data_Science/3-05_knn.md new file mode 100644 index 0000000..5fdf591 --- /dev/null +++ b/Fundamentals_of_Accelerated_Data_Science/3-05_knn.md @@ -0,0 +1,19 @@ +lazy learner +деревья для поиска ближайших значений (KD, Q, R, Ball) + +- k-dimensional tree +Recursively splits data along coordinate axes. +at each node pick a dimension, split at median, each node becomes a hyperrectangle in d-dimensional space. + +- Quad-Tree +Each node is a square region. If too many points fall into a region subdivide into 4 equal quadrants + +- rectangle tree +Each node stores several children, each with a Minimum Bounding Rectangle covering many points or objects. Subtrees group spatially close objects. Insertions try to minimize rectangle enlargement. + +- Ball-Tree +Each node contains: + - a center point + - a radius enclosing all points in that node +Two children represent two balls that split the data + |