feat(knn): add k-Nearest Neighbors classifier - #105
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Implements a kNN classifier that leverages existing LSI infrastructure for similarity computations. Unlike Bayes which requires training, kNN uses instance-based learning—store examples and classify by finding the most similar ones. Key features: - Hash-style API consistent with Bayes and LSI (add, classify) - classify_with_neighbors() returns interpretable results with neighbor details, vote tallies, and confidence scores - Distance-weighted voting option for more nuanced classification - Full JSON/Marshal serialization and storage backend support - Handles edge cases like single-item classifiers gracefully This completes Issue #103 and provides a third classification algorithm suited for small datasets where interpretability matters. Closes #103
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Greptile SummaryImplements k-Nearest Neighbors classifier by leveraging existing LSI infrastructure for similarity calculations. Uses instance-based learning where examples are stored and classification happens by finding the k most similar items and voting by their categories. Major Changes
Key Features
ArchitectureThe implementation cleanly delegates to LSI for similarity calculations ( Confidence Score: 5/5
Important Files Changed
Sequence DiagramsequenceDiagram
participant User
participant KNN
participant LSI
participant Matrix
Note over User,Matrix: Adding Training Data
User->>KNN: add(spam: ["Buy now!"], ham: ["Meeting"])
KNN->>KNN: synchronize { @dirty = true }
KNN->>LSI: add(**items)
LSI->>LSI: Store items with categories
LSI->>LSI: Mark for rebuild if auto_rebuild
LSI-->>KNN: Items stored
Note over User,Matrix: Classification Flow
User->>KNN: classify("Free offer!")
KNN->>KNN: classify_with_neighbors(text)
KNN->>KNN: synchronize block
alt Empty classifier
KNN-->>User: nil
else Has items
KNN->>KNN: find_neighbors(text)
KNN->>LSI: proximity_array_for_content(text)
LSI->>LSI: synchronize { proximity_array_for_content_unlocked }
alt Single item
LSI-->>KNN: [[item, 1.0]]
else Multiple items
LSI->>LSI: node_for_content_unlocked(text)
LSI->>Matrix: Compute dot products with all items
Matrix-->>LSI: Similarity scores
LSI->>LSI: Sort by similarity descending
LSI-->>KNN: [[item1, 0.92], [item2, 0.75], ...]
end
KNN->>KNN: Select top k neighbors
KNN->>LSI: categories_for(each item)
LSI-->>KNN: Category labels
KNN->>KNN: tally_votes(neighbors)
alt Weighted voting
KNN->>KNN: votes[cat] += similarity
else Unweighted voting
KNN->>KNN: votes[cat] += 1.0
end
KNN->>KNN: Calculate winner & confidence
KNN-->>User: {category: "spam", neighbors: [...], votes: {...}, confidence: 0.85}
end
Note over User,Matrix: Persistence
User->>KNN: save_to_file(path)
KNN->>KNN: to_json
KNN->>KNN: as_json
KNN->>LSI: as_json
LSI-->>KNN: LSI state as hash
KNN->>KNN: Write JSON to file
KNN->>KNN: @dirty = false
KNN-->>User: Bytes written
User->>KNN: load_from_file(path)
KNN->>KNN: from_json(File.read)
KNN->>LSI: from_json(lsi_data)
LSI-->>KNN: Restored LSI instance
KNN-->>User: Restored KNN instance
|
![greptile-apps[bot]](https://avatars.githubusercontent.com/in/867647?s=60&v=4){kind=small}
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| # This class implements a k-Nearest Neighbors classifier that leverages | ||
| # the existing LSI infrastructure for similarity computations. | ||
| # | ||
| # Unlike traditional classifiers that require training, kNN uses instance-based | ||
| # learning - it stores examples and classifies by finding the most similar ones. | ||
| # | ||
| # Example usage: | ||
| # knn = Classifier::KNN.new(k: 3) | ||
| # knn.add("spam" => ["Buy now!", "Limited offer!"]) | ||
| # knn.add("ham" => ["Meeting tomorrow", "Project update"]) | ||
| # knn.classify("Special discount!") # => "spam" |
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style: docstring restates obvious implementation details
Suggested change
| # This class implements a k-Nearest Neighbors classifier that leverages | |
| # the existing LSI infrastructure for similarity computations. | |
| # | |
| # Unlike traditional classifiers that require training, kNN uses instance-based | |
| # learning - it stores examples and classifies by finding the most similar ones. | |
| # | |
| # Example usage: | |
| # knn = Classifier::KNN.new(k: 3) | |
| # knn.add("spam" => ["Buy now!", "Limited offer!"]) | |
| # knn.add("ham" => ["Meeting tomorrow", "Project update"]) | |
| # knn.classify("Special discount!") # => "spam" | |
| # k-Nearest Neighbors classifier using LSI for similarity. | |
| # | |
| # Example: | |
| # knn = Classifier::KNN.new(k: 3) | |
| # knn.add(spam: ["Buy now!"], ham: ["Meeting tomorrow"]) | |
| # knn.classify("Special discount!") # => "spam" |
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Path: lib/classifier/knn.rb
Line: 12:22
Comment:
**style:** docstring restates obvious implementation details
```suggestion
# k-Nearest Neighbors classifier using LSI for similarity.
#
# Example:
# knn = Classifier::KNN.new(k: 3)
# knn.add(spam: ["Buy now!"], ham: ["Meeting tomorrow"])
# knn.classify("Special discount!") # => "spam"
```
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| # Creates a new kNN classifier. | ||
| # | ||
| # @param k [Integer] Number of neighbors to consider (default: 5) | ||
| # @param weighted [Boolean] Use distance-weighted voting (default: false) | ||
| # |
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style: docstring repeats parameter types already in @rbs
Suggested change
| # Creates a new kNN classifier. | |
| # | |
| # @param k [Integer] Number of neighbors to consider (default: 5) | |
| # @param weighted [Boolean] Use distance-weighted voting (default: false) | |
| # | |
| # @rbs (?k: Integer, ?weighted: bool) -> void |
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Path: lib/classifier/knn.rb
Line: 36:40
Comment:
**style:** docstring repeats parameter types already in `@rbs`
```suggestion
# @rbs (?k: Integer, ?weighted: bool) -> void
```
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|
|
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| # Adds labeled examples to the classifier using hash-style syntax. | ||
| # Keys are categories, values are items (or arrays of items). | ||
| # | ||
| # @example Single item per category | ||
| # knn.add("spam" => "Buy now!") | ||
| # knn.add("ham" => "Meeting tomorrow") | ||
| # | ||
| # @example Multiple items per category | ||
| # knn.add("spam" => ["Buy now!", "Limited offer!"]) | ||
| # | ||
| # @example Batch operations | ||
| # knn.add( | ||
| # "spam" => ["Buy now!", "Limited offer!"], | ||
| # "ham" => ["Meeting tomorrow", "Project update"] | ||
| # ) | ||
| # |
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style: docstring examples repeat what method signature already shows
Suggested change
| # Adds labeled examples to the classifier using hash-style syntax. | |
| # Keys are categories, values are items (or arrays of items). | |
| # | |
| # @example Single item per category | |
| # knn.add("spam" => "Buy now!") | |
| # knn.add("ham" => "Meeting tomorrow") | |
| # | |
| # @example Multiple items per category | |
| # knn.add("spam" => ["Buy now!", "Limited offer!"]) | |
| # | |
| # @example Batch operations | |
| # knn.add( | |
| # "spam" => ["Buy now!", "Limited offer!"], | |
| # "ham" => ["Meeting tomorrow", "Project update"] | |
| # ) | |
| # | |
| # @rbs (**untyped items) -> void |
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Path: lib/classifier/knn.rb
Line: 51:67
Comment:
**style:** docstring examples repeat what method signature already shows
```suggestion
# @rbs (**untyped items) -> void
```
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| # Classifies the given text by finding the k nearest neighbors | ||
| # and using majority voting. | ||
| # | ||
| # @param text [String] The text to classify | ||
| # @return [String, Symbol, nil] The predicted category, or nil if no examples exist | ||
| # |
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style: docstring restates method name and signature
Suggested change
| # Classifies the given text by finding the k nearest neighbors | |
| # and using majority voting. | |
| # | |
| # @param text [String] The text to classify | |
| # @return [String, Symbol, nil] The predicted category, or nil if no examples exist | |
| # | |
| # @rbs (String) -> (String | Symbol)? |
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Path: lib/classifier/knn.rb
Line: 87:92
Comment:
**style:** docstring restates method name and signature
```suggestion
# @rbs (String) -> (String | Symbol)?
```
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| # Classifies the given text and returns detailed information about | ||
| # the neighbors that contributed to the decision. | ||
| # | ||
| # @param text [String] The text to classify | ||
| # @return [Hash] A hash containing: | ||
| # - :category - The predicted category | ||
| # - :neighbors - Array of neighbor details (item, category, similarity) | ||
| # - :votes - Hash of category => vote count/weight | ||
| # - :confidence - Confidence score (winning vote share) | ||
| # |
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style: docstring restates return hash keys visible in code
Suggested change
| # Classifies the given text and returns detailed information about | |
| # the neighbors that contributed to the decision. | |
| # | |
| # @param text [String] The text to classify | |
| # @return [Hash] A hash containing: | |
| # - :category - The predicted category | |
| # - :neighbors - Array of neighbor details (item, category, similarity) | |
| # - :votes - Hash of category => vote count/weight | |
| # - :confidence - Confidence score (winning vote share) | |
| # | |
| # Returns category, neighbors, votes, and confidence score. | |
| # | |
| # @rbs (String) -> Hash[Symbol, untyped] |
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Path: lib/classifier/knn.rb
Line: 99:108
Comment:
**style:** docstring restates return hash keys visible in code
```suggestion
# Returns category, neighbors, votes, and confidence score.
#
# @rbs (String) -> Hash[Symbol, untyped]
```
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| synchronize do | ||
| @k = data['k'] | ||
| @weighted = data['weighted'] |
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style: docstring repeats method name and obvious behavior
Suggested change
| synchronize do | |
| @k = data['k'] | |
| @weighted = data['weighted'] | |
| # @rbs (Array[Hash[Symbol, untyped]]) -> Hash[String | Symbol, Float] |
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Path: lib/classifier/knn.rb
Line: 352:354
Comment:
**style:** docstring repeats method name and obvious behavior
```suggestion
# @rbs (Array[Hash[Symbol, untyped]]) -> Hash[String | Symbol, Float]
```
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| def classify_with_neighbors(text) | ||
| synchronize do | ||
| return empty_result if @lsi.items.empty? | ||
|
|
||
| neighbors = find_neighbors(text) | ||
| return empty_result if neighbors.empty? | ||
|
|
||
| votes = tally_votes(neighbors) | ||
| winner = votes.max_by { |_, v| v }&.first | ||
| total_votes = votes.values.sum | ||
| confidence = winner && total_votes.positive? ? votes[winner] / total_votes.to_f : 0.0 | ||
|
|
||
| { | ||
| category: winner, | ||
| neighbors: neighbors, | ||
| votes: votes, | ||
| confidence: confidence | ||
| } | ||
| end |
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style: nested conditionals - use early returns
Suggested change
| def classify_with_neighbors(text) | |
| synchronize do | |
| return empty_result if @lsi.items.empty? | |
| neighbors = find_neighbors(text) | |
| return empty_result if neighbors.empty? | |
| votes = tally_votes(neighbors) | |
| winner = votes.max_by { |_, v| v }&.first | |
| total_votes = votes.values.sum | |
| confidence = winner && total_votes.positive? ? votes[winner] / total_votes.to_f : 0.0 | |
| { | |
| category: winner, | |
| neighbors: neighbors, | |
| votes: votes, | |
| confidence: confidence | |
| } | |
| end | |
| def classify_with_neighbors(text) | |
| synchronize do | |
| return empty_result if @lsi.items.empty? | |
| neighbors = find_neighbors(text) | |
| return empty_result if neighbors.empty? | |
| votes = tally_votes(neighbors) | |
| winner = votes.max_by { |_, v| v }&.first | |
| return empty_result unless winner | |
| total_votes = votes.values.sum | |
| confidence = total_votes.positive? ? votes[winner] / total_votes.to_f : 0.0 | |
| { | |
| category: winner, | |
| neighbors: neighbors, | |
| votes: votes, | |
| confidence: confidence | |
| } | |
| end | |
| end |
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Path: lib/classifier/knn.rb
Line: 110:128
Comment:
**style:** nested conditionals - use early returns
```suggestion
def classify_with_neighbors(text)
synchronize do
return empty_result if @lsi.items.empty?
neighbors = find_neighbors(text)
return empty_result if neighbors.empty?
votes = tally_votes(neighbors)
winner = votes.max_by { |_, v| v }&.first
return empty_result unless winner
total_votes = votes.values.sum
confidence = total_votes.positive? ? votes[winner] / total_votes.to_f : 0.0
{
category: winner,
neighbors: neighbors,
votes: votes,
confidence: confidence
}
end
end
```
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| # @rbs () -> bool | ||
| def dirty? | ||
| @dirty | ||
| end | ||
|
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| # Loads a classifier from configured storage. | ||
| # | ||
| # @param storage [Storage::Base] The storage to load from | ||
| # @return [KNN] The loaded classifier | ||
| # |
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style: nested conditionals - use early returns
Suggested change
| # @rbs () -> bool | |
| def dirty? | |
| @dirty | |
| end | |
| # Loads a classifier from configured storage. | |
| # | |
| # @param storage [Storage::Base] The storage to load from | |
| # @return [KNN] The loaded classifier | |
| # | |
| def reload | |
| raise ArgumentError, 'No storage configured' unless storage | |
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
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Path: lib/classifier/knn.rb
Line: 246:256
Comment:
**style:** nested conditionals - use early returns
```suggestion
def reload
raise ArgumentError, 'No storage configured' unless storage
raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
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|
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| instance = from_json(data) | ||
| instance.storage = storage | ||
| instance | ||
| end | ||
|
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| # Loads a classifier from a file. | ||
| # | ||
| # @param path [String] The file path | ||
| # @return [KNN] The loaded classifier |
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style: nested conditionals - use early returns
Suggested change
| instance = from_json(data) | |
| instance.storage = storage | |
| instance | |
| end | |
| # Loads a classifier from a file. | |
| # | |
| # @param path [String] The file path | |
| # @return [KNN] The loaded classifier | |
| def reload! | |
| raise ArgumentError, 'No storage configured' unless storage | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
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Path: lib/classifier/knn.rb
Line: 261:270
Comment:
**style:** nested conditionals - use early returns
```suggestion
def reload!
raise ArgumentError, 'No storage configured' unless storage
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
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| @k, @weighted, @lsi, @dirty = data | ||
| @storage = nil | ||
| end | ||
|
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| private | ||
|
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| # Finds the k nearest neighbors for the given text. | ||
| # |
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style: nested conditionals - use early returns
Suggested change
| @k, @weighted, @lsi, @dirty = data | |
| @storage = nil | |
| end | |
| private | |
| # Finds the k nearest neighbors for the given text. | |
| # | |
| def self.load(storage:) | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| instance = from_json(data) | |
| instance.storage = storage | |
| instance | |
| end |
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Path: lib/classifier/knn.rb
Line: 285:292
Comment:
**style:** nested conditionals - use early returns
```suggestion
def self.load(storage:)
data = storage.read
raise StorageError, 'No saved state found' unless data
instance = from_json(data)
instance.storage = storage
instance
end
```
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| # LSI requires at least 2 items to build an index | ||
| # For single item, return it directly with a default similarity | ||
| if @lsi.items.size == 1 | ||
| item = @lsi.items.first | ||
| return [{ | ||
| item: item, | ||
| category: @lsi.categories_for(item).first, | ||
| similarity: 1.0 | ||
| }] | ||
| end |
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style: nested conditional with defensive code for single-item case. LSI already handles this - remove the special case.
Suggested change
| # LSI requires at least 2 items to build an index | |
| # For single item, return it directly with a default similarity | |
| if @lsi.items.size == 1 | |
| item = @lsi.items.first | |
| return [{ | |
| item: item, | |
| category: @lsi.categories_for(item).first, | |
| similarity: 1.0 | |
| }] | |
| end | |
| def find_neighbors(text) | |
| proximity = @lsi.proximity_array_for_content(text) | |
| neighbors = proximity.reject { |item, _| item == text }.first(@k) | |
| neighbors.map do |item, similarity| | |
| { | |
| item: item, | |
| category: @lsi.categories_for(item).first, | |
| similarity: similarity | |
| } | |
| end | |
| end |
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Path: lib/classifier/knn.rb
Line: 295:304
Comment:
**style:** nested conditional with defensive code for single-item case. LSI already handles this - remove the special case.
```suggestion
def find_neighbors(text)
proximity = @lsi.proximity_array_for_content(text)
neighbors = proximity.reject { |item, _| item == text }.first(@k)
neighbors.map do |item, similarity|
{
item: item,
category: @lsi.categories_for(item).first,
similarity: similarity
}
end
end
```
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How can I resolve this? If you propose a fix, please make it concise.| # | ||
| # @rbs () -> void | ||
| def save | ||
| raise ArgumentError, 'No storage configured. Use save_to_file(path) or set storage=' unless storage |
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style: defensive error for impossible scenario - if storage is nil, the method already can't be called. Remove this check.
Suggested change
| raise ArgumentError, 'No storage configured. Use save_to_file(path) or set storage=' unless storage | |
| storage.write(to_json) |
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Path: lib/classifier/knn.rb
Line: 200:200
Comment:
**style:** defensive error for impossible scenario - if storage is nil, the method already can't be called. Remove this check.
```suggestion
storage.write(to_json)
```
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| raise ArgumentError, 'No storage configured' unless storage | ||
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty |
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style: nested error checks - use early returns
Suggested change
| raise ArgumentError, 'No storage configured' unless storage | |
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | |
| def reload | |
| raise ArgumentError, 'No storage configured' unless storage | |
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
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Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 222:223
Comment:
**style:** nested error checks - use early returns
```suggestion
def reload
raise ArgumentError, 'No storage configured' unless storage
raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
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How can I resolve this? If you propose a fix, please make it concise.
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| raise ArgumentError, 'No storage configured' unless storage | ||
|
|
||
| data = storage.read | ||
| raise StorageError, 'No saved state found' unless data |
Contributor
There was a problem hiding this comment.
style: nested error checks - use early returns
Suggested change
| raise ArgumentError, 'No storage configured' unless storage | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| def reload! | |
| raise ArgumentError, 'No storage configured' unless storage | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 237:240
Comment:
**style:** nested error checks - use early returns
```suggestion
def reload!
raise ArgumentError, 'No storage configured' unless storage
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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| data = storage.read | ||
| raise StorageError, 'No saved state found' unless data |
Contributor
There was a problem hiding this comment.
style: nested error check - use early return
Suggested change
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| def self.load(storage:) | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| instance = from_json(data) | |
| instance.storage = storage | |
| instance | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 259:260
Comment:
**style:** nested error check - use early return
```suggestion
def self.load(storage:)
data = storage.read
raise StorageError, 'No saved state found' unless data
instance = from_json(data)
instance.storage = storage
instance
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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| synchronize do | ||
| @k = data['k'] | ||
| @weighted = data['weighted'] | ||
|
|
||
| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' | ||
| @lsi = LSI.from_json(lsi_data) | ||
| @dirty = false | ||
| end |
Contributor
There was a problem hiding this comment.
style: synchronize block wraps entire method body - move the guard clause outside
Suggested change
| synchronize do | |
| @k = data['k'] | |
| @weighted = data['weighted'] | |
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' | |
| @lsi = LSI.from_json(lsi_data) | |
| @dirty = false | |
| end | |
| def restore_from_json(json) | |
| data = JSON.parse(json) | |
| raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn' | |
| synchronize do | |
| @k = data['k'] | |
| @weighted = data['weighted'] | |
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' | |
| @lsi = LSI.from_json(lsi_data) | |
| @dirty = false | |
| end | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 352:360
Comment:
**style:** synchronize block wraps entire method body - move the guard clause outside
```suggestion
def restore_from_json(json)
data = JSON.parse(json)
raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn'
synchronize do
@k = data['k']
@weighted = data['weighted']
lsi_data = data['lsi']
lsi_data['type'] = 'lsi'
@lsi = LSI.from_json(lsi_data)
@dirty = false
end
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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| # Restore the LSI from its nested data | ||
| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json |
Contributor
There was a problem hiding this comment.
logic: unnecessary mutation of passed data - work with local copy
Suggested change
| # Restore the LSI from its nested data | |
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' |
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 186:188
Comment:
**logic:** unnecessary mutation of passed data - work with local copy
```suggestion
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
```
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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to
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| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' |
Contributor
There was a problem hiding this comment.
logic: unnecessary mutation of parsed data - work with local copy
Suggested change
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 356:357
Comment:
**logic:** unnecessary mutation of parsed data - work with local copy
```suggestion
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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| neighbors.each do |neighbor| | ||
| category = neighbor[:category] | ||
| next unless category |
Contributor
There was a problem hiding this comment.
style: guard clause inside loop - extract to method or combine with map logic
Suggested change
| neighbors.each do |neighbor| | |
| category = neighbor[:category] | |
| next unless category | |
| neighbors.each do |neighbor| | |
| category = neighbor[:category] | |
| weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0 | |
| votes[category] += weight if category | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 324:326
Comment:
**style:** guard clause inside loop - extract to method or combine with map logic
```suggestion
neighbors.each do |neighbor|
category = neighbor[:category]
weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0
votes[category] += weight if category
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Owner
Author
|
@greptile please re-review |
Comment on lines
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| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json |
Contributor
There was a problem hiding this comment.
logic: mutates the passed-in hash by adding 'type' key, violating principle of least surprise
Suggested change
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 137:138
Comment:
**logic:** mutates the passed-in hash by adding `'type'` key, violating principle of least surprise
```suggestion
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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to
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| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' |
Contributor
There was a problem hiding this comment.
logic: mutates the parsed hash, same issue as line 137
Suggested change
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' |
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 285:286
Comment:
**logic:** mutates the parsed hash, same issue as line 137
```suggestion
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
```
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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| # LSI requires at least 2 items to build an index | ||
| # For single item, return it directly with a default similarity | ||
| if @lsi.items.size == 1 | ||
| item = @lsi.items.first | ||
| return [{ | ||
| item: item, | ||
| category: @lsi.categories_for(item).first, | ||
| similarity: 1.0 | ||
| }] | ||
| end |
Contributor
There was a problem hiding this comment.
style: unnecessary special case - LSI's proximity_array_for_content should handle single-item case internally
If LSI requires this workaround, that's an LSI bug to fix there, not something to paper over here
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Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 228:237
Comment:
**style:** unnecessary special case - LSI's `proximity_array_for_content` should handle single-item case internally
If LSI requires this workaround, that's an LSI bug to fix there, not something to paper over here
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.| category = neighbor[:category] | ||
| next unless category | ||
|
|
||
| weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0 |
Contributor
There was a problem hiding this comment.
style: [neighbor[:similarity], 0.0].max is defensive - similarity from LSI should never be negative. If it is, that's a bug in LSI
Suggested change
| weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0 | |
| weight = @weighted ? neighbor[:similarity] : 1.0 |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 259:259
Comment:
**style:** `[neighbor[:similarity], 0.0].max` is defensive - similarity from LSI should never be negative. If it is, that's a bug in LSI
```suggestion
weight = @weighted ? neighbor[:similarity] : 1.0
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
+136
to
+138
| # Restore the LSI from its nested data | ||
| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json |
Contributor
There was a problem hiding this comment.
style: comment repeats what code shows - the code is self-documenting
Suggested change
| # Restore the LSI from its nested data | |
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' # Ensure type is set for LSI.from_json | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 136:138
Comment:
**style:** comment repeats what code shows - the code is self-documenting
```suggestion
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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to
+174
| def reload | ||
| raise ArgumentError, 'No storage configured' unless storage | ||
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | ||
|
|
||
| data = storage.read | ||
| raise StorageError, 'No saved state found' unless data | ||
|
|
||
| restore_from_json(data) | ||
| @dirty = false | ||
| self |
Contributor
There was a problem hiding this comment.
style: nested error checks - use early returns
Suggested change
| def reload | |
| raise ArgumentError, 'No storage configured' unless storage | |
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| def reload | |
| raise ArgumentError, 'No storage configured' unless storage | |
| raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 165:174
Comment:
**style:** nested error checks - use early returns
```suggestion
def reload
raise ArgumentError, 'No storage configured' unless storage
raise UnsavedChangesError, 'Unsaved changes would be lost. Call save first or use reload!' if @dirty
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
+179
to
+187
| def reload! | ||
| raise ArgumentError, 'No storage configured' unless storage | ||
|
|
||
| data = storage.read | ||
| raise StorageError, 'No saved state found' unless data | ||
|
|
||
| restore_from_json(data) | ||
| @dirty = false | ||
| self |
Contributor
There was a problem hiding this comment.
style: nested error checks - use early returns
Suggested change
| def reload! | |
| raise ArgumentError, 'No storage configured' unless storage | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| def reload! | |
| raise ArgumentError, 'No storage configured' unless storage | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| restore_from_json(data) | |
| @dirty = false | |
| self | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 179:187
Comment:
**style:** nested error checks - use early returns
```suggestion
def reload!
raise ArgumentError, 'No storage configured' unless storage
data = storage.read
raise StorageError, 'No saved state found' unless data
restore_from_json(data)
@dirty = false
self
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
+197
to
+203
| def self.load(storage:) | ||
| data = storage.read | ||
| raise StorageError, 'No saved state found' unless data | ||
|
|
||
| instance = from_json(data) | ||
| instance.storage = storage | ||
| instance |
Contributor
There was a problem hiding this comment.
style: nested error check - use early return
Suggested change
| def self.load(storage:) | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| instance = from_json(data) | |
| instance.storage = storage | |
| instance | |
| def self.load(storage:) | |
| data = storage.read | |
| raise StorageError, 'No saved state found' unless data | |
| instance = from_json(data) | |
| instance.storage = storage | |
| instance | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 197:203
Comment:
**style:** nested error check - use early return
```suggestion
def self.load(storage:)
data = storage.read
raise StorageError, 'No saved state found' unless data
instance = from_json(data)
instance.storage = storage
instance
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
+255
to
+261
| neighbors.each do |neighbor| | ||
| category = neighbor[:category] | ||
| next unless category | ||
|
|
||
| weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0 | ||
| votes[category] += weight | ||
| end |
Contributor
There was a problem hiding this comment.
style: guard clause inside loop - combine with map logic or extract to method
Suggested change
| neighbors.each do |neighbor| | |
| category = neighbor[:category] | |
| next unless category | |
| weight = @weighted ? [neighbor[:similarity], 0.0].max : 1.0 | |
| votes[category] += weight | |
| end | |
| neighbors.each do |neighbor| | |
| category = neighbor[:category] or next | |
| weight = @weighted ? neighbor[:similarity] : 1.0 | |
| votes[category] += weight | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 255:261
Comment:
**style:** guard clause inside loop - combine with map logic or extract to method
```suggestion
neighbors.each do |neighbor|
category = neighbor[:category] or next
weight = @weighted ? neighbor[:similarity] : 1.0
votes[category] += weight
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Comment on lines
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to
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| def restore_from_json(json) | ||
| data = JSON.parse(json) | ||
| raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn' | ||
|
|
||
| synchronize do | ||
| @k = data['k'] | ||
| @weighted = data['weighted'] | ||
|
|
||
| lsi_data = data['lsi'] | ||
| lsi_data['type'] = 'lsi' | ||
| @lsi = LSI.from_json(lsi_data) | ||
| @dirty = false | ||
| end | ||
| end |
Contributor
There was a problem hiding this comment.
style: synchronize block wraps entire method - move guard clause outside
Suggested change
| def restore_from_json(json) | |
| data = JSON.parse(json) | |
| raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn' | |
| synchronize do | |
| @k = data['k'] | |
| @weighted = data['weighted'] | |
| lsi_data = data['lsi'] | |
| lsi_data['type'] = 'lsi' | |
| @lsi = LSI.from_json(lsi_data) | |
| @dirty = false | |
| end | |
| end | |
| def restore_from_json(json) | |
| data = JSON.parse(json) | |
| raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn' | |
| synchronize do | |
| @k = data['k'] | |
| @weighted = data['weighted'] | |
| lsi_data = data['lsi'].dup | |
| lsi_data['type'] = 'lsi' | |
| @lsi = LSI.from_json(lsi_data) | |
| @dirty = false | |
| end | |
| end |
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: lib/classifier/knn.rb
Line: 277:290
Comment:
**style:** `synchronize` block wraps entire method - move guard clause outside
```suggestion
def restore_from_json(json)
data = JSON.parse(json)
raise ArgumentError, "Invalid classifier type: #{data['type']}" unless data['type'] == 'knn'
synchronize do
@k = data['k']
@weighted = data['weighted']
lsi_data = data['lsi'].dup
lsi_data['type'] = 'lsi'
@lsi = LSI.from_json(lsi_data)
@dirty = false
end
end
```
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.- Fix LSI single-item bug instead of working around in KNN - Remove defensive max(0) check on similarity scores - Use early return for nil winner - Simplify guard clause with 'or next' - Condense class docstring - Avoid mutating input hash with .dup
Owner
Author
|
Addressed the actionable feedback - thanks! Re: remaining comments - these are intentionally kept:
The removed ones were YARD tags ( @greptile please re-review |
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Summary
add,classify)classify_with_neighbors()returns interpretable results with neighbor detailsweighted: true)Usage
When to Use kNN vs Bayes vs LSI
Test plan
Closes #103