sklearn.metrics.confusion_matrix - TypeError: 'numpy.ndarray' object is not callable

Question

I seem to be getting an error when calling confusion_matrix, please see below. How can I get this to work?

from sklearn.metrics import confusion_matrix
confusion_matrix = confusion_matrix(normalisedArr_y5,predicted5)

The DataTypes are as follows predicted5 Int64 (244,) array([1,1,1,...,2,2,2]) normalisedArr_y5 Int64 (244,) array([1,1,1,...,5,5,5]) — Garch2017
– Garch2017, Commented Mar 27, 2017 at 12:21
You are redefining confusion_matrix - use a different variable name. — AChampion
– AChampion, Commented Mar 27, 2017 at 17:37

J. Doe · Accepted Answer · 2017-12-14 10:45:01Z

2

1 Be sure that both values are np arrays or lists as specified by @Roelant
2 do not assign to your variable's name the same name as the function name

from sklearn.metrics import confusion_matrix
cfm = confusion_matrix(normalisedArr_y5,predicted5)
print(cfm)

answered Dec 14, 2017 at 10:45

J. Doe

3,6443 gold badges26 silver badges44 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Roelant · Accepted Answer · 2017-03-27 12:27:50Z

1

Both normalisedArr_y5 and predicted5 should be np.arrays or lists. Apparently one or both are not. You could try:

confusion_matrix = confusion_matrix(normalisedArr_y5.tolist(),predicted5.tolist())

answered Mar 27, 2017 at 12:27

Roelant

5,2295 gold badges43 silver badges77 bronze badges

Aneez Ahmed · Accepted Answer · 2019-02-03 07:38:58Z

0

In my case, I was defining

normalisedArr_x5 = df.iloc[:,:-1]

and

normalisedArr_y5 = data.iloc[:,-1:]

and this Error was coming.

So just check if both the dataframe variables are the same (here df) and perform the steps again @Garch2017

answered Feb 3, 2019 at 7:38

Aneez Ahmed

1231 silver badge6 bronze badges