From d5963b2da7fff2b1883d8868d61127b62bac165e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 23 Oct 2024 15:34:22 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 machine_learning/ridge_regression/model.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/machine_learning/ridge_regression/model.py b/machine_learning/ridge_regression/model.py
index 6a1470c5c..b0908f9ef 100644
--- a/machine_learning/ridge_regression/model.py
+++ b/machine_learning/ridge_regression/model.py
@@ -3,11 +3,12 @@ import pandas as pd
 
 
 class RidgeRegression:
-    def __init__(self,
-            alpha: float = 0.001,
-            regularization_param: float = 0.1,
-            num_iterations: int = 1000,
-            ) -> None:
+    def __init__(
+        self,
+        alpha: float = 0.001,
+        regularization_param: float = 0.1,
+        num_iterations: int = 1000,
+    ) -> None:
         self.alpha: float = alpha
         self.regularization_param: float = regularization_param
         self.num_iterations: int = num_iterations
@@ -49,10 +50,9 @@ class RidgeRegression:
         m = len(y)
 
         predictions = x_scaled.dot(self.theta)
-        cost = (
-            1 / (2 * m)) * np.sum((predictions - y) ** 2) + (
-                self.regularization_param / (2 * m)
-                ) * np.sum(self.theta**2)
+        cost = (1 / (2 * m)) * np.sum((predictions - y) ** 2) + (
+            self.regularization_param / (2 * m)
+        ) * np.sum(self.theta**2)
         return cost
 
     def mean_absolute_error(self, y_true: np.ndarray, y_pred: np.ndarray) -> float: