piyush-bhardwaj/breast-cancer-diagnosis-using-machine-learning

Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.

breast-cancer-diagnosis-using-machine-learning's Issues

unable to plot graph

Making the Confusion Matrix

from sklearn.metrics import confusion_matrix
cm_KNN = confusion_matrix(y_test, y_pred)
print(cm_KNN)
print("Accuracy score of train KNN")
print(accuracy_score(y_train, trained_model.predict(X_train))*100)
print("Accuracy score of test KNN")
print(accuracy_score(y_test, y_pred)*100)
knn.append(accuracy_score(y_test, y_pred)*100)
plt.figure(figsize=(12, 6))
plt.plot(range(1, 21),knn, color='red', linestyle='dashed', marker='o',
markerfacecolor='blue', markersize=10)
plt.title('Accuracy for different K Value')
plt.xlabel('K Value')
plt.ylabel('Accuracy')

the error

---

ValueError Traceback (most recent call last)
in
11 plt.figure(figsize=(12, 6))
12 plt.plot(range(1, 21),knn, color='red', linestyle='dashed', marker='o',
---> 13 markerfacecolor='blue', markersize=10)
14 plt.title('Accuracy for different K Value')
15 plt.xlabel('K Value')

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\pyplot.py in plot(scalex, scaley, data, *args, **kwargs)
2794 return gca().plot(
2795 *args, scalex=scalex, scaley=scaley, **({"data": data} if data
-> 2796 is not None else {}), **kwargs)
2797
2798

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_axes.py in plot(self, scalex, scaley, data, *args, **kwargs)
1663 """
1664 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D._alias_map)
-> 1665 lines = [*self._get_lines(*args, data=data, **kwargs)]
1666 for line in lines:
1667 self.add_line(line)

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_base.py in call(self, *args, **kwargs)
223 this += args[0],
224 args = args[1:]
--> 225 yield from self._plot_args(this, kwargs)
226
227 def get_next_color(self):

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_base.py in _plot_args(self, tup, kwargs)
389 x, y = index_of(tup[-1])
390
--> 391 x, y = self._xy_from_xy(x, y)
392
393 if self.command == 'plot':

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_base.py in _xy_from_xy(self, x, y)
268 if x.shape[0] != y.shape[0]:
269 raise ValueError("x and y must have same first dimension, but "
--> 270 "have shapes {} and {}".format(x.shape, y.shape))
271 if x.ndim > 2 or y.ndim > 2:
272 raise ValueError("x and y can be no greater than 2-D, but have "

ValueError: x and y must have same first dimension, but have shapes (20,) and (3,)

pls help me