scikit-learn

Fix Python – sklearn error ValueError: Input contains NaN, infinity or a value too large for dtype(‘float64’)

by

I am using sklearn and having a problem with the affinity propagation. I have built an input matrix and I keep getting the following error.
ValueError: Input contains NaN, infinity or a value too large for dtype(‘float64’).

I have run
np.isnan(mat.any()) #and gets False
np.isfinite(mat.all()) #and gets True

I tried using
mat[np.isfinite(mat) ==….

Fix Python – Save classifier to disk in scikit-learn

by

How do I save a trained Naive Bayes classifier to disk and use it to predict data?
I have the following sample program from the scikit-learn website:
from sklearn import datasets
iris = datasets.load_iris()
from sklearn.naive_bayes import GaussianNB
gnb = GaussianNB()
y_pred = gnb.fit(iris.data, iris.target).predict(iris.data)
print “Number of mis….

Fix Python – How to normalize a NumPy array to a unit vector?

by

I would like to convert a NumPy array to a unit vector. More specifically, I am looking for an equivalent version of this normalisation function:
def normalize(v):
norm = np.linalg.norm(v)
if norm == 0:
return v
return v / norm

This function handles the situation where vector v has the norm value of 0.
Is there any similar fun….