Re: [Scikit-learn-general] Using a cluster algorithm ex-post as predictor

2012-11-12 Thread Peter Prettenhofer
Here is the reference:: http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html#sklearn.cluster.KMeans.predict 2012/11/12 Andreas Mueller : > Hi Christian. > Some clustering algorithm (for example KMeans and MiniBatchKMeans) > provide a "predict" function, which you can use t

Re: [Scikit-learn-general] Using a cluster algorithm ex-post as predictor

2012-11-12 Thread Andreas Mueller
Hi Christian. Some clustering algorithm (for example KMeans and MiniBatchKMeans) provide a "predict" function, which you can use to label new data. Not all algorithms support this as there is not always an obvious way to assign labels to new points (for example I don't know of any using mean-shift)

[Scikit-learn-general] Using a cluster algorithm ex-post as predictor

2012-11-12 Thread Christian
Hi, after fitting a clusterer I'll label new data. Is there an easier way instead of building an ex-post classifier. Many thanks Christian example in weka: #Building the clusterer and save the object in cluster.cla java -cp weka.jar weka.clusterers.EM -t data0.arff -d cluster.cla === Cluste

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Lars Buitinck
2012/11/12 : > zip(dataDescrs_name,dataDescrs_array) > > will do the job? I have to admit that I have lost the overview in my large > dataset :) It will do *a* job -- I don't really understand what you're after, but try that expression to see if it produces what you need. -- Lars Buitinck Scien

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Paul . Czodrowski
> 2012/11/12 : > > Actually I would like to name the features. Sorry for the confusion! > > What do you want to use it for? If you have a sample x (a row from X) > and a list of n_features names for your features, then > > zip(names_of_features, x) > > will give you a list of (name, value) pa

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Lars Buitinck
2012/11/12 : > Actually I would like to name the features. Sorry for the confusion! What do you want to use it for? If you have a sample x (a row from X) and a list of n_features names for your features, then zip(names_of_features, x) will give you a list of (name, value) pairs for the feat

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Paul . Czodrowski
Dear Andy, > Hi Paul. > I am a bit confused. Do you want to name targets or features? Actually I would like to name the features. Sorry for the confusion! But since you mentioned it: Naming the targets would also be very helpful! > > Also, what does it mean to dump out the leaves of an RF? What

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Peter Prettenhofer
2012/11/12 : > > Dear SciKitters, > > given an array of (n_samples,n_features) -> How do I assign target_names in > a concluding step? > > The target_names are stored in a list and, of course, have the same order > as the n_features vector. > > In a next step, I would like to dump out the importan

Re: [Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Andreas Mueller
Hi Paul. I am a bit confused. Do you want to name targets or features? Also, what does it mean to dump out the leaves of an RF? What information do you want to get? The RF can compute feature importance with the transform method, if that is what you are after. For visualizing which features are i

[Scikit-learn-general] set target_names / importance of features in a trained model

2012-11-12 Thread Paul . Czodrowski
Dear SciKitters, given an array of (n_samples,n_features) -> How do I assign target_names in a concluding step? The target_names are stored in a list and, of course, have the same order as the n_features vector. In a next step, I would like to dump out the importance of the most relevant featur