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adding more
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@ -18,7 +18,7 @@ public class DistancedItemQueue<U, T> implements Iterable<DistancedItem<T>> {
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private final PriorityQueue<DistancedItem<T>> queue;
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private final boolean minQueue;
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/**
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* Creates ontainer for items with their distances.
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* Creates container for items with their distances.
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*
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* @param origin Origin (reference) point
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* @param initial Initial list of elements to add in the structure
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@ -94,7 +94,7 @@ public class DistancedItemQueue<U, T> implements Iterable<DistancedItem<T>> {
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}
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/**
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* Dequeue all the elements from queueu with ordering mantained
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* Dequeue all the elements from queue with ordering maintained
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*
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* @return remove all the elements in the order of the queue i.e min/max queue.
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*/
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@ -105,7 +105,7 @@ object SerializableBruteForceIndex {
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}
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/**
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* This is a class that wrapps a BruteForceIndex and provides a method for serialization.
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* This is a class that wraps a BruteForceIndex and provides a method for serialization.
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*
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* @param bruteForceIndex all queries and updates are sent to this index.
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* @param embeddingInjection injection that can convert embeddings to thrift embeddings.
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@ -18,7 +18,7 @@ object TypedHnswIndex {
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* construction, but better index quality. At some point, increasing
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* ef_construction does not improve the quality of the index. One way to
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* check if the selection of ef_construction was ok is to measure a recall
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* for M nearest neighbor search when ef = ef_constuction: if the recall is
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* for M nearest neighbour search when ef = ef_construction: if the recall is
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* lower than 0.9, than there is room for improvement.
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* @param maxM The number of bi-directional links created for every new element during construction.
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* Reasonable range for M is 2-100. Higher M work better on datasets with high
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@ -64,7 +64,7 @@ object TypedHnswIndex {
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* construction, but better index quality. At some point, increasing
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* ef_construction does not improve the quality of the index. One way to
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* check if the selection of ef_construction was ok is to measure a recall
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* for M nearest neighbor search when ef = ef_constuction: if the recall is
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* for M nearest neighbour search when ef = ef_constuction: if the recall is
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* lower than 0.9, than there is room for improvement.
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* @param maxM The number of bi-directional links created for every new element during construction.
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* Reasonable range for M is 2-100. Higher M work better on datasets with high
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