From 7381dfa0b4602b41a51b0d183772bb7f20e78d8b Mon Sep 17 00:00:00 2001
From: Usrer1 <user1@gmail.com>
Date: Thu, 30 Oct 2025 23:17:06 +0530
Subject: [PATCH 1/2] Add svm.py to machine_learning

---
 machine_learning/svm.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 machine_learning/svm.py

diff --git a/machine_learning/svm.py b/machine_learning/svm.py
new file mode 100644
index 000000000000..4fbd07b8bd64
--- /dev/null
+++ b/machine_learning/svm.py
@@ -0,0 +1,32 @@
+from sklearn.model_selection import GridSearchCV
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+from sklearn.svm import SVC
+from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
+from sklearn.datasets import load_breast_cancer
+data=load_breast_cancer()
+X,y=data.data,data.target
+
+X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=42)
+
+param_grid={
+    'C':[1, 10],
+    'kernel':['linear','rbf'],
+    'gamma':['scale']
+}
+
+svm=SVC(random_state=42)
+
+grid_search=GridSearchCV(svm, param_grid, cv=3, scoring='accuracy', n_jobs=-1, verbose=1)
+grid_search.fit(X_train,y_train)
+
+print("Best parameters:",grid_search.best_params_)
+print("Best cross validation score",grid_search.best_score_)
+
+best_svm=grid_search.best_estimator_
+y_pred=best_svm.predict(X_test)
+test_accuracy=accuracy_score(y_test,y_pred)
+print(f"Test accuracy:,{test_accuracy:.2f}")
+

From 19378c6590776b37d9788ddfe4474dd75c6f0bf0 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 30 Oct 2025 17:52:13 +0000
Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 machine_learning/svm.py | 34 +++++++++++++++++-----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/machine_learning/svm.py b/machine_learning/svm.py
index 4fbd07b8bd64..9e03a2306706 100644
--- a/machine_learning/svm.py
+++ b/machine_learning/svm.py
@@ -6,27 +6,27 @@
 from sklearn.svm import SVC
 from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
 from sklearn.datasets import load_breast_cancer
-data=load_breast_cancer()
-X,y=data.data,data.target
 
-X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=42)
+data = load_breast_cancer()
+X, y = data.data, data.target
 
-param_grid={
-    'C':[1, 10],
-    'kernel':['linear','rbf'],
-    'gamma':['scale']
-}
+X_train, X_test, y_train, y_test = train_test_split(
+    X, y, test_size=0.3, random_state=42
+)
 
-svm=SVC(random_state=42)
+param_grid = {"C": [1, 10], "kernel": ["linear", "rbf"], "gamma": ["scale"]}
 
-grid_search=GridSearchCV(svm, param_grid, cv=3, scoring='accuracy', n_jobs=-1, verbose=1)
-grid_search.fit(X_train,y_train)
+svm = SVC(random_state=42)
 
-print("Best parameters:",grid_search.best_params_)
-print("Best cross validation score",grid_search.best_score_)
+grid_search = GridSearchCV(
+    svm, param_grid, cv=3, scoring="accuracy", n_jobs=-1, verbose=1
+)
+grid_search.fit(X_train, y_train)
 
-best_svm=grid_search.best_estimator_
-y_pred=best_svm.predict(X_test)
-test_accuracy=accuracy_score(y_test,y_pred)
-print(f"Test accuracy:,{test_accuracy:.2f}")
+print("Best parameters:", grid_search.best_params_)
+print("Best cross validation score", grid_search.best_score_)
 
+best_svm = grid_search.best_estimator_
+y_pred = best_svm.predict(X_test)
+test_accuracy = accuracy_score(y_test, y_pred)
+print(f"Test accuracy:,{test_accuracy:.2f}")