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``` python
n,p = 2194, 12277
X = np.random.normal(0, 1, (n, p))
y = X[:,1] + X[:,2] + np.random.normal(0,1, n)
l1 = LassoLarsCV(n_jobs=1).fit(X,y)
print(l1.coef_)
l = LassoLarsCV(n_jobs=-1).fit(X,y)…
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Hi, I am interested in ML as a complement to physically-based models to predict some molecular properties from relatively small datasets (~100-1000 data points). For now I started using TPOT from comm…
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#### Summary:
Let's say we have a model
`fit1
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#### Description
I search to test ensemble learning classifiers with imbalanced data under the same conditions (cross validation and estimator params for example). Among them, there are the B…
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May I ask that how to do cross-validation in Neupy? I have checked the sklearn website and I still feel so confused.
After applying the cross_val_score, the error shows as:
`
TypeError: If no …
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I tried to execute the main.py but it shows a single classification report, I need the SVM result and also need the mean accuracy. How can I execute to get these output?
Please reply asap
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In the lecture, the sample code of KFold, it doesn't work due to miss typo.
1. try `from sklearn.cross_validation import KFold`, but it is a deprecation and will remove 0.20.0 version.
2. alt versio…
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Hi scikit-learners,
I have a problem using the `train_test_split` with binarized labels in a multilabel setting. Specifically, I tried to use the `stratify` parameter to even out the data between …
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Hi everyone,
Maybe it has already been done before but I was wondering whether anyone has shown that Meka and the results obtained through the Meka wrapper are the same, if not similar?
As a tes…
ekyy2 updated
6 years ago
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so once we get csrmatrix and vocab we call cross_validation_accuracy(). when we use KFOLD(n,n_folds) where n_folds=5 and n is the size of the csr_matrix?