unable to plot graph

[jspjai]

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