Trying to plot the decision Boundary of the k-NN Classifier but is unable to do so getting TypeError: '(slice(None, None, None), 0)' is an invalid key
h = .01 # step size in the mesh
# Create color maps
cmap_light = ListedColormap(['#FFAAAA', '#AAFFAA', '#AAAAFF','#AFAFAF'])
cmap_bold = ListedColormap(['#FF0000', '#00FF00', '#0000FF','#AFAFAF'])
for weights in ['uniform', 'distance']:
# we create an instance of Neighbours Classifier and fit the data.
clf = KNeighborsClassifier(n_neighbors=6, weights=weights)
clf.fit(X_train, y_train)
# Plot the decision boundary. For that, we will assign a color to each
# point in the mesh [x_min, x_max]x[y_min, y_max].
x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(x_min, x_max, h),
np.arange(y_min, y_max, h))
Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
# Put the result into a color plot
Z = Z.reshape(xx.shape)
plt.figure()
plt.pcolormesh(xx, yy, Z, cmap=cmap_light)
# Plot also the training points
plt.scatter(X[:, 0], X[:, 1], c=y, cmap=cmap_bold)
plt.xlim(xx.min(), xx.max())
plt.ylim(yy.min(), yy.max())
plt.title("4-Class classification (k = %i, weights = '%s')"
% (n_neighbors, weights))
plt.show()
Got this when running not very sure what it means dont think the clf.fit have a problem but I am not sure
TypeError Traceback (most recent call last)
<ipython-input-394-bef9b05b1940> in <module>
12 # Plot the decision boundary. For that, we will assign a color to each
13 # point in the mesh [x_min, x_max]x[y_min, y_max].
---> 14 x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1
15 y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
16 xx, yy = np.meshgrid(np.arange(x_min, x_max, h),
~\Miniconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
2925 if self.columns.nlevels > 1:
2926 return self._getitem_multilevel(key)
-> 2927 indexer = self.columns.get_loc(key)
2928 if is_integer(indexer):
2929 indexer = [indexer]
~\Miniconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
2654 'backfill or nearest lookups')
2655 try:
-> 2656 return self._engine.get_loc(key)
2657 except KeyError:
2658 return self._engine.get_loc(self._maybe_cast_indexer(key))
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
TypeError: '(slice(None, None, None), 0)' is an invalid key
Since you are trying to access directly as array, you are getting that issue. Try this:
from sklearn.impute import SimpleImputer
imputer = SimpleImputer(missing_values = np.nan, strategy = 'mean',verbose=0)
imputer = imputer.fit(X.iloc[:, 1:3])
X.iloc[:, 1:3] = imputer.transform(X.iloc[:, 1:3])