I am trying to plot a decision boundary for logistic regression but i got this error :
TypeError: scatter() got multiple values for argument 's'
Here is my code :
logreg = LogisticRegression()
logreg.fit(X_train,y_train)
b = logreg.intercept_[0]
w1, w2 = logreg.coef_.T
c = -b/w2
m = -w1/w2
# Plot the data and the classification with the decision boundary.
xmin, xmax = -1, 2
ymin, ymax = -1, 2.5
xd = np.array([xmin, xmax])
yd = m*xd + c
plt.plot(xd, yd, 'k', lw=1, ls='--')
plt.fill_between(xd, yd, ymin, color='tab:blue', alpha=0.2)
plt.fill_between(xd, yd, ymax, color='tab:orange', alpha=0.2)
plt.scatter(*X[y==0].T, s=8, alpha=0.5)
plt.scatter(*X[y==1].T, s=8, alpha=0.5)
plt.xlim(xmin, xmax)
plt.ylim(ymin, ymax)
plt.show()
Since i am a beginner i would also like to know if there is possibility to plot my logistic regression including all features or something else (2 most important features). I had to choose only 2 columns here.
EDIT : I also got this error :
TypeError: scatter() takes from 2 to 13 positional arguments but 1715 were given
For your information :
X = df
X = X.drop(columns=['answer']) #features
y = df['answer'] #target
X.shape # (4948, 2)
y.shape # (4948,)
X[y==0].shape # (1715,2)
Any help would be appreciated ! Thanks.
The problem is with the shape of what you are trying to plot, namely, X[y==0]
. Here I recreate a 1715x2 matrix with the same shape, and try to scatter()
it:
import numpy as np
from matplotlib import pyplot as plt
x = np.random.rand(1715, 2)
print(np.shape(x)) # (1715, 2)
plt.scatter(*x, s= 8)
I get a TypeError: scatter() got multiple values for argument 's'
.
However, if I transpose it:
x = np.random.rand(1715, 2)
print(np.shape(x))
plt.scatter(*x.T, s= 8)
plt.show()
I get:
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