Address additional code review feedback

- Change normalize guard from `< EPSILON` to `<= 0.0` - only return zero
  vector for actual zero magnitude, not near-zero values
- Use `val.abs` with EPSILON threshold for singular values to handle
  small negative values from floating point errors more robustly
- Update test to reflect correct behavior: near-zero vectors normalize
  to unit vectors, only true zero vectors return zero

Author: cardmagic

lib/classifier/extensions/vector.rb

@@ -29,8 +29,8 @@ def magnitude
 
   def normalize
     magnitude_value = magnitude
-    # Return zero vector if magnitude is too small to safely divide
-    return Vector[*Array.new(size, 0.0)] if magnitude_value < EPSILON
+    # Return zero vector only if magnitude is zero or numerically negative
+    return Vector[*Array.new(size, 0.0)] if magnitude_value <= 0.0
 
     normalized_values = []
     size.times do |i|
@@ -102,7 +102,7 @@ def SV_decomp(max_sweeps = 20)
     q_rotation_matrix.row_size.times do |r|
       # Guard against negative values due to floating point errors
       val = q_rotation_matrix[r, r].to_f
-      singular_values << Math.sqrt(val.negative? ? 0.0 : val)
+      singular_values << Math.sqrt(val < -Vector::EPSILON ? 0.0 : val.abs)
     end
 
     # Replace near-zero singular values with EPSILON to prevent division by zero

test/extensions/word_hash_test.rb

@@ -125,13 +125,17 @@ def test_normalize_zero_vector_returns_zero_vector
     assert_in_delta 0.0, normalized[2], 0.001
   end
 
-  def test_normalize_near_zero_vector_returns_zero_vector
+  def test_normalize_near_zero_vector_returns_unit_vector
+    # Near-zero vectors should still normalize to unit vectors
+    # Only actual zero vectors return zero
     vec = Vector[1e-15, 1e-15, 1e-15]
     normalized = vec.normalize
 
-    assert_in_delta 0.0, normalized[0], 0.001
-    assert_in_delta 0.0, normalized[1], 0.001
-    assert_in_delta 0.0, normalized[2], 0.001
+    # Should normalize to [1/sqrt(3), 1/sqrt(3), 1/sqrt(3)]
+    expected = 1.0 / Math.sqrt(3)
+    assert_in_delta expected, normalized[0], 0.001
+    assert_in_delta expected, normalized[1], 0.001
+    assert_in_delta expected, normalized[2], 0.001
   end
 end