擅长:python、mysql、java
<p>我也是0.18.0。这就是我尝试过的,而且成功了。这就是你在做的吗?你知道吗</p>
<pre><code>import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
Y = np.array([1, 1, 1, 2, 2, 2])
from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(X,Y)
import pandas as pd
data = pd.DataFrame(X)
data['y']=Y
predictions = pd.DataFrame([dict(zip(clf.classes_, l)) for l in clf.predict_proba(X)])
pd.concat([data, predictions], axis=1, ignore_index=True)
0 1 2 3 4
0 -1 -1 1 1.000000e+00 1.522998e-08
1 -2 -1 1 1.000000e+00 3.775135e-11
2 -3 -2 1 1.000000e+00 5.749523e-19
3 1 1 2 1.522998e-08 1.000000e+00
4 2 1 2 3.775135e-11 1.000000e+00
5 3 2 2 5.749523e-19 1.000000e+00
</code></pre>