From 18b0277e6246b00a45db2b34e61c53b322428772 Mon Sep 17 00:00:00 2001
From: QuantumNovice <43876848+QuantumNovice@users.noreply.github.com>
Date: Sat, 2 May 2020 19:57:24 +0500
Subject: [PATCH 1/2] Update support_vector_machines.py

---
 machine_learning/support_vector_machines.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/machine_learning/support_vector_machines.py b/machine_learning/support_vector_machines.py
index 53b446ef975d..4b389fb7cb53 100644
--- a/machine_learning/support_vector_machines.py
+++ b/machine_learning/support_vector_machines.py
@@ -12,7 +12,7 @@ def NuSVC(train_x, train_y):
 
 
 def Linearsvc(train_x, train_y):
-    svc_linear = svm.LinearSVC()
+    svc_linear = svm.LinearSVC(tol=10e-2)
     svc_linear.fit(train_x, train_y)
     return svc_linear
 
@@ -20,7 +20,7 @@ def Linearsvc(train_x, train_y):
 def SVC(train_x, train_y):
     # svm.SVC(C=1.0, kernel='rbf', degree=3, gamma=0.0, coef0=0.0, shrinking=True,
     # probability=False,tol=0.001, cache_size=200, class_weight=None, verbose=False,
-    # max_iter=-1, random_state=None)
+    # max_iter=1000, random_state=None)
     # various parameters like "kernel","gamma","C" can effectively tuned for a given
     # machine learning model.
     SVC = svm.SVC(gamma="auto")
@@ -39,7 +39,6 @@ def test(X_new):
     'versicolor'
     >>> test([6,3,4,1])
     'versicolor'
-
     """
     iris = load_iris()
     # splitting the dataset to test and train
@@ -51,6 +50,7 @@ def test(X_new):
     # current_model=NuSVC(train_x, train_y)
     current_model = Linearsvc(train_x, train_y)
     prediction = current_model.predict([X_new])
+
     return iris["target_names"][prediction][0]
 
 

From f27710fb031c779fd577266e3e07945c40927230 Mon Sep 17 00:00:00 2001
From: Christian Clauss <cclauss@me.com>
Date: Sat, 2 May 2020 21:18:57 +0200
Subject: [PATCH 2/2] Update support_vector_machines.py

---
 machine_learning/support_vector_machines.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/machine_learning/support_vector_machines.py b/machine_learning/support_vector_machines.py
index 4b389fb7cb53..3bf54a69128d 100644
--- a/machine_learning/support_vector_machines.py
+++ b/machine_learning/support_vector_machines.py
@@ -1,7 +1,6 @@
 from sklearn.datasets import load_iris
 from sklearn import svm
 from sklearn.model_selection import train_test_split
-import doctest
 
 
 # different functions implementing different types of SVM's
@@ -50,9 +49,10 @@ def test(X_new):
     # current_model=NuSVC(train_x, train_y)
     current_model = Linearsvc(train_x, train_y)
     prediction = current_model.predict([X_new])
-
     return iris["target_names"][prediction][0]
 
 
 if __name__ == "__main__":
+    import doctest
+
     doctest.testmod()