New answers tagged scikit-learn
2
votes
Accepted
Python SK-Learn KNN Imputer ( "ValueError: could not convert string to float: )
After replacing the ? with np.NaN, you will be able to convert the type of the BareNuc ...
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Why is my test accuracy higher than train accuracy? SKLEARN
As Oxbowerce mentioned already above. It is possible to have a test score that is higher than the training score. This is not an over-fitting scenario as well. Because your training score is lower ...
2
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Accepted
Number of stop words variation in libaries sklearn and nltk
general agreement [on] stop words
No, the definition is fuzzy and situational.
We apply stop words according to the need.
Even in sklearn, you might choose to tack on
additional stop words for a ...
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1
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Any Interface/Library that can take the Python ML code and run on spark cluster without learning PySpark?
There's a library called joblib-spark that you can use to leverage a Spark cluster. It lets you take the Scikit-learn code you've written and train it in a distributed, parallel way across a Spark ...
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Solve a non-linear system, in Python, with the GAUSS-NEWTON algorithm? (Jacobian matrix J, etc.)
Python mathematical libraries numpy and scipy have routines for solving systems of linear equations: ...
- 101
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Out-of-Range Target Variable in Sequence-based Machine Learning Model
"Interpolation is easy. Extrapolation is hard."
Extrapolating might be the right thing to do.
But always be suspect of a model that is leading
you to big unexplored regions of the state ...
- 488
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Scikit-learn and TensorFlow with very different MLP models
I know that your question was asked almost a year ago, but still maybe someone will find it useful.
There are two problems:
The first is you are using softmax activation, yet only have one output ...
- 3
1
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Accepted
How do I best approach a multiple-target binary classification in Tensorflow/Keras?
The term you would use for that is "multilabel classification".
It is certainly possible to do so in Tensorflow, although I would say it is more frequent to see it in examples of image ...
- 23.8k
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Scikit-Learn classifiers have impressively bad accuracy on test set for binary text classification problem
Gaussian Naive Bayes
GaussianNB assumes that your features (input data) follow a normal distribution (or Gaussian distribution) for both classes of your binary ...
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Does it make sense to train data in scikit-learn and copy+paste parameters into Rust's linfa?
Or, to make things easier and robust, you can export the trained scikit-learn model in a cross-platform format, and import it in Rust.
2 suggested format by scikit-learn are ONNX and PMML. Chances are ...
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Does it make sense to train data in scikit-learn and copy+paste parameters into Rust's linfa?
In theory, if you were to pass the same data through a logistic regression or a SVM implemented in different packages, you should get the same results. And the same should apply when tuning a model in ...
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