Initial commit

h03_robust_kernels.py

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+import math
+from typing import Dict
+from abc import ABC, abstractmethod
+
+class IRobustKernels(ABC):
+    @abstractmethod
+    def huber_loss(self, error: float, threshold: float) -> float: pass
+    @abstractmethod
+    def cauchy_loss(self, error: float, k: float) -> float: pass
+    @abstractmethod
+    def compute_weight(self, error: float, kernel_type: str, params: Dict[str, float]) -> float: pass
+
+class RobustKernels(IRobustKernels):
+    """H03: Huber/Cauchy loss functions for outlier rejection in optimization."""
+    def huber_loss(self, error: float, threshold: float) -> float:
+        abs_err = abs(error)
+        if abs_err <= threshold:
+            return 0.5 * (error ** 2)
+        return threshold * (abs_err - 0.5 * threshold)
+
+    def cauchy_loss(self, error: float, k: float) -> float:
+        return (k ** 2 / 2.0) * math.log(1.0 + (error / k) ** 2)
+
+    def compute_weight(self, error: float, kernel_type: str, params: Dict[str, float]) -> float:
+        abs_err = abs(error)
+        if abs_err < 1e-8: return 1.0
+        
+        if kernel_type.lower() == "huber":
+            threshold = params.get("threshold", 1.0)
+            return 1.0 if abs_err <= threshold else threshold / abs_err
+        elif kernel_type.lower() == "cauchy":
+            k = params.get("k", 1.0)
+            return 1.0 / (1.0 + (error / k) ** 2)
+        return 1.0