[Scikit-learn-general] Jeff Levesque: check SVM dataset large enough

Hi all, Just curious if there is a standardized set of algorithms which can be run, specifically to test whether the supplied dataset is large enough for the respective kernel choice in SVM? Is there an implementation, or Python method within scikit-learn that can perform these sort of tests?

Re: [Scikit-learn-general] Jeff Levesque: '.predict_proba()' me tho for smaller datasets

Hi Jeff, In general, most implementations of predict_proba are some proxy the conditional probability p(y|x). Some of them really are modelling this quantity quite well (e.g., gaussian process) while for some others it is closer to a heuristic than to the actual p(y|x) (e.g., with linear models).

Re: [Scikit-learn-general] Jeff Levesque: '.predict_proba()' me tho for smaller datasets

On 12/01/2015 11:28 PM, Jeff Levesque wrote: > Is there a way to determine if the data used with the SVC class, used to > generate an SVM model, would generate a poor model, or confidence percentage > (or 'decision_function', if that's preferred)? > > I don't understand the question. ---

Re: [Scikit-learn-general] Jeff Levesque: '.predict_proba()' me tho for smaller datasets

Is there a way to determine if the data used with the SVC class, used to generate an SVM model, would generate a poor model, or confidence percentage (or 'decision_function', if that's preferred)? Jeffrey Levesque https://github.com/jeff1evesque/ (603) 969-5363 Sent from my iPhone > On Dec 1,

Re: [Scikit-learn-general] Jeff Levesque: '.predict_proba()' me tho for smaller datasets

I don't understand the question. By definition this function provides probability estimates. In the case of SVC, it is possible that these probabilities don't coincide with the prediction. You could make predictions using the probabilities if you'd liked. There is no other way to ensure consisten

[Scikit-learn-general] Jeff Levesque: confidence on classification prediction

Hello all, I have three general questions regarding generating a confidence percentage on a classification prediction: 1. can calibration / brier score loss, be used for a multi-class classification? The scikit-learn page (http://scikit-learn.org/stable/auto_examples/calibration/plot_c

[Scikit-learn-general] Jeff Levesque: '.predict_proba()' me tho for smaller datasets

Hey all, I have a specific question: how do I ensure that the '.predict_proba()' method, associated with the classification sklearn, accurately provides probability, that a provided value is one of the predefined class: https://github.com/jeff1evesque/machine-learning/issues/1924#issuecomment

[Scikit-learn-general] Jeff Levesque:

Hi all, I have a specific question: how do I ensure that the '.predict_proba()' method, associated with the classification sklearn, accurately provides probability, that a provided value is one of the predefined class: https://github.com/jeff1evesque/machine-learning/issues/1924#issuecomment-15

[Scikit-learn-general] Jeff Levesque: Scikit-Learn web / programmatic interface

Hey all, I'm currently working on a web / programmatic interface to scikit-learn: https://github.com/jeff1evesque/machine-learning I've just release v0.2 earlier yesterday: https://github.com/jeff1evesque/machine-learning/releases This project needs a lot of attention, and numerous issues need

Re: [Scikit-learn-general] Jeff Levesque: Prototype Interface (API) to sklearn

Hi Jeff. Do you have a hosted version? That is more likely to get feedback. Andy -- ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists

[Scikit-learn-general] Jeff Levesque: Prototype Interface (API) to sklearn

To whom it may concern, I’ve created a prototype interface (web-interface, and API) to the scikit-learn classification algorithm. It will undergo many iterations of improvement, since I’m still working on milestone 0.2,and there is about 5 more milestone slated: - https://github.com