Update ARIMA time series Model

Author: ai-nerdy

machine_learning/adaboost.py

@@ -12,8 +12,9 @@
 array([0, 1])
 """
 
+from typing import Any
+
 import numpy as np
-from typing import Any, Dict, List
 
 
 class AdaBoost:
@@ -23,8 +24,8 @@ def __init__(self, n_estimators: int = 50) -> None:
             n_estimators: Number of boosting rounds.
         """
         self.n_estimators: int = n_estimators
-        self.alphas: List[float] = []  # Weights for each weak learner
-        self.models: List[Dict[str, Any]] = []  # List of weak learners (stumps)
+        self.alphas: list[float] = []  # Weights for each weak learner
+        self.models: list[dict[str, Any]] = []  # List of weak learners (stumps)
 
     def fit(self, feature_matrix: np.ndarray, target: np.ndarray) -> None:
         """Fit AdaBoost model.
@@ -77,11 +78,11 @@ def _build_stump(
         feature_matrix: np.ndarray,
         target_signed: np.ndarray,
         sample_weights: np.ndarray,
-    ) -> Dict[str, Any]:
+    ) -> dict[str, Any]:
         """Find the best decision stump for current weights."""
         n_samples, n_features = feature_matrix.shape
         min_error = float("inf")
-        best_stump: Dict[str, Any] = {}
+        best_stump: dict[str, Any] = {}
         for feature in range(n_features):
             thresholds = np.unique(feature_matrix[:, feature])
             for threshold in thresholds:

machine_learning/arima.py

@@ -12,8 +12,8 @@
 array([10.99999999, 12.00000001])
 """
 
+
 import numpy as np
-from typing import Optional
 
 
 class ARIMAModel:
@@ -27,8 +27,8 @@ def __init__(self, ar_order: int = 1, diff_order: int = 0, ma_order: int = 0) ->
         self.ar_order = ar_order
         self.diff_order = diff_order
         self.ma_order = ma_order
-        self.coef_: Optional[np.ndarray] = None
-        self.resid_: Optional[np.ndarray] = None
+        self.coef_: np.ndarray | None = None
+        self.resid_: np.ndarray | None = None
 
     def difference(self, time_series: np.ndarray, order: int) -> np.ndarray:
         """Apply differencing to make series stationary."""