I am using MLPClassifier in python and I am trying to use the loss_curve_ attribute but I have this error "'MLPClassifier' object has no attribute 'loss_curve_' ". Any ideas of what import I need? I have already tried the "from sklearn import metrics" but it didnt work.
Related
I tried the below line of code, but it is giving me the below error
y = rnn_cell_impl._linear(slot_inputs, attn_size, True)
AttributeError: module 'tensorflow.python.ops.rnn_cell_impl' has no attribute '_linear'
I am currently using Tensorflow version 2.10, I tried with all possible solutions by using
#from tensorflow.contrib.rnn.python.ops import core_rnn_cell
or
#from tensorflow.keras.layers import RNN
still no solution.
Can someone help me with the same?
I have imported norm as:
from scipy.stats import norm
I want to find out the version using:
print(scipy.__version__)
but it is raising an error called:
NameError: name 'scipy' is not defined
if i am using this:
print(norm.__version__)
but it is raising another error called:
AttributeError: 'norm_gen' object has no attribute '__version__'
Please help me to solve this issue.
Thanks
The line from scipy.stats import norm doesn't make the name scipy available in your current namespace. To use scipy.__version__, you must first import scipy.
In [57]: import scipy
In [58]: print(scipy.__version__)
1.4.1
import pandas as pd
import scipy.sparse
_vectorized = count_vectorizer.transform(data['text'])
_dataframe = pd.DataFrame.sparse.from_spmatrix(_vectorized)
Why is the error occuring. I'm working on Jupyter based environment kaggle and azure notebook. Error shows up both of the place. But On spyder it's working perfectly. What am I missing?
Try this:
_dataframe = pd.SparseDataFrame(_vectorized)
I'm starting learning basic feature extraction with librosa and was trying reading and storing ten kick drums with pathlib, but it doesn't work since I always getting an encoding error, where as there is no error without pathlib.
I tried changing the path, updating every imported library very often, using wav instead of mp3 but had no further idea.
My code:
%matplotlib inline
from pathlib import Path
import numpy, scipy, matplotlib.pyplot as plt, sklearn, urllib, IPython.display as ipd
import librosa, librosa.display
kick_signals = [
librosa.load(p)[0] for p in Path().glob('audio/drum_samples/train/kick_*.mp3')
]
Error messages:
RuntimeError: Error opening 'audio/techno-nine_o_three.mp3': File contains data in an unknown format.
and
AttributeError: 'PosixPath' object has no attribute 'encode'
I would be very thankful, if you would and could help me.
You can convert the PossixPath object to a string, using p.as_posix()
Example:
p = Path(file_path)
p.as_posix()
Try:
kick_signals = [
librosa.load(p.absolute())[0] for p in Path().glob('audio/drum_samples/train/kick_*.mp3')
]
That way you pass a string instead of a PosixPath to librosa.
If that does not fix it, check your mp3 file. Does it play in a regular player? If not, please post the whole error message (stacktrace). Perhaps librosa's dependencies aren't installed properly.
I am getting this error when trying our rasa_nlu with spacy
AttributeError: 'sklearn_crfsuite' object has no attribute 'CRF'
rasa_nlu was importing this way
import sklearn_crfsuite
So I tried importing like below before calling rasa_nlu
from sklearn_crfsuite import CRF
But getting a different
error - cannot import name 'CRF'
Looking for some suggestions.
If you want to do sklearn_crfsuite.CRF, then do import sklearn_crfsuite to import it. If you're importing with from sklearn_crfsuite import CRF, then just use CRF by itself.