I’m getting this weird error:
classification.py:1113: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no predicted samples.
‘precision’, ‘predicted’, average, warn_for)`
but then it also prints the f-score the first time I run:
metrics.f1_score(y_test, y_pred, average=’weighted’)
The second time I run, it prov….
I want to plot a confusion matrix to visualize the classifer’s performance, but it shows only the numbers of the labels, not the labels themselves:
from sklearn.metrics import confusion_matrix
import pylab as pl
y_test=[‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business’, ‘business….
I have the following code to test some of most popular ML algorithms of sklearn python library:
import numpy as np
from sklearn import metrics, svm
from sklearn.linear_model import LinearRegression
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeC….
I need to split my data into a training set (75%) and test set (25%). I currently do that with the code below:
X, Xt, userInfo, userInfo_train = sklearn.cross_validation.train_test_split(X, userInfo)
However, I’d like to stratify my training dataset. How do I do that? I’ve been looking into the StratifiedKFold method, but doesn’t let me specif….
Background: I’m just getting started with scikit-learn, and read at the bottom of the page about joblib, versus pickle.
it may be more interesting to use joblib’s replacement of pickle (joblib.dump & joblib.load), which is more efficient on big data, but can only pickle to the disk and not to a string
I read this Q&A on Pickle,
Common use-case….
I am getting the following error while trying to import from sklearn:
>>> from sklearn import svm
Traceback (most recent call last):
File “
from sklearn import svm
File “C:\Python27\lib\site-packages\sklearn\__init__.py”, line 16, in
from . import check_build
ImportError: cannot import name che….
In shell script I am checking whether this packages are installed or not, if not installed then install it. So withing shell script:
import nltk
echo nltk.__version__
but it stops shell script at import line
in linux terminal tried to see in this manner:
which nltk
which gives nothing thought it is installed.
Is there any other way to verify thi….
I am using GridSearch from sklearn to optimize parameters of the classifier. There is a lot of data, so the whole process of optimization takes a while: more than a day. I would like to watch the performance of the already-tried combinations of parameters during the execution. Is it possible?
….
I am using the logistic regression function from sklearn, and was wondering what each of the solver is actually doing behind the scenes to solve the optimization problem.
Can someone briefly describe what “newton-cg”, “sag”, “lbfgs” and “liblinear” are doing?
….
I want to apply scaling (using StandardScaler() from sklearn.preprocessing) to a pandas dataframe. The following code returns a numpy array, so I lose all the column names and indeces. This is not what I want.
features = df[[“col1”, “col2”, “col3”, “col4”]]
autoscaler = StandardScaler()
features = autoscaler.fit_transform(features)
A “solution” I….