This might happen inside scikit, and it depends on what you’re doing. I recommend reading the documentation for the functions you’re using. You might be using one which depends e.g. on your matrix being positive definite and not fulfilling that criteria. EDIT: How could I miss that: is obviously wrong. Right would be: and You … Read more
This might happen inside scikit, and it depends on what you’re doing. I recommend reading the documentation for the functions you’re using. You might be using one which depends e.g. on your matrix being positive definite and not fulfilling that criteria. EDIT: How could I miss that: is obviously wrong. Right would be: and
That isn’t how you set parameters in xgboost. You would either want to pass your param grid into your training function, such as xgboost’s train or sklearn’s GridSearchCV, or you would want to use your XGBClassifier’s set_params method. Another thing to note is that if you’re using xgboost’s wrapper to sklearn (ie: the XGBClassifier() or … Read more
If you have a list of lists, you only needed to use … per this LINK in the scipy / numpy documentation. You just needed to define dtype inside the call to asarray.
I’ve seen other posts talking about this but anyone of these can help me. I am using jupyter notebook with Python 3.6.0 on windows x6 machine. I have a large dataset but I keep only a piece of it to run my models: This is a piece of code that i used: When I run … Read more
You are passing floats to a classifier which expects categorical values as the target vector. If you convert it to int it will be accepted as input (although it will be questionable if that’s the right way to do it). It would be better to convert your training scores by using scikit’s labelEncoder function. The … Read more
As pointed out by @amit-gupta in the question above, sklearn.cross_validation has been deprecated. The function train_test_split can now be found here: Simply replace the import statement from the question to the one above.
It must relate to the renaming and deprecation of cross_validation sub-module to model_selection. Try substituting cross_validation to model_selection
It must relate to the renaming and deprecation of cross_validation sub-module to model_selection. Try substituting cross_validation to model_selection