Re: [Scikit-learn-general] nested cross validation to get unbiased results

to run 10 processes on 4 processors if it makes sense!? > > > > On May 12, 2016, at 10:26 PM, Amita Misra wrote: > > > > I had not thought about the n_jobs parameter, mainly because it does not > run on my mac and the system just hangs if i use it. > > The same

Re: [Scikit-learn-general] nested cross validation to get unbiased results

cc = accuracy_score(y_true=y_train[outer_valid_idx], > y_pred=y_pred) > > print(' | inner ACC %.2f%% | outer ACC %.2f%%' % > (gs_est.best_score_ * 100, acc * 100)) > > cv_scores[name].append(acc) > > > > However, it should essentially

Re: [Scikit-learn-general] nested cross validation to get unbiased results

; cv_scores[name].append(acc) > > However, it should essentially do the same thing as your code if I see it > correctly. > > > > On May 12, 2016, at 4:50 PM, Amita Misra wrote: > > > > Actually I do not have an independent test set and hence I want to use > it a

Re: [Scikit-learn-general] nested cross validation to get unbiased results

> More details about it you should be able to find in documentation: > > • > http://scikit-learn.org/stable/modules/grid_search.html#grid-search > > • > http://scikit-learn.org/stable/modules/grid_search.html#gridsearch-scoring > > > > 2016-05-12 17:05 GMT+0

[Scikit-learn-general] nested cross validation to get unbiased results

validation. Inner folds CV over training data involves a grid search over hyperparameters and outer folds evaluate the performance. Thanks, Amita-- Amita Misra Graduate Student Researcher Natural Language and Dialogue Systems Lab Baskin School of Engineering University of California Santa Cruz

Re: [Scikit-learn-general] using Support vector regression/gaussian regression with a Pearson VII function kernel

rth illustrating in an example >> >> >> On Thu, Mar 31, 2016 at 7:45 PM, Sebastian Raschka < >> se.rasc...@gmail.com> wrote: >> >>> Seems like that the GaussianProcess class only has an autocorrelation >>> parameter, but when I understand correctly, the auto

[Scikit-learn-general] using Support vector regression/gaussian regression with a Pearson VII function kernel

(Puk Kernel) for support vector and Gaussian regression? Thanks, Amita -- Amita Misra Graduate Student Researcher Natural Language and Dialogue Systems Lab Baskin School of Engineering University of California Santa Cruz

Re: [Scikit-learn-general] precomputed distance matrix for clustering

tObj.fit_predict(Sim) My concern is that here I used a similarity function , and I think as per documents it should be a disimilarity matrix, how can I change it to dissimilarity matrix. Also what would be a more efficient way to do this. Thanks, Amita On Wed, Sep 3, 2014 at 12:50 AM, Amita Mi

[Scikit-learn-general] precomputed distance matrix for clustering

Hello, I have n documents and want to use precomputed similarity mertric between a pair of documents for clustering. I created a 2 dim numpy Array say X, containing similarity score for every pair of documents. Also type(X) and X.shape gives the output as (n, n) Then I create a cluster object us

Re: [Scikit-learn-general] Runtime warning scikit 0.15, warning for numpy

Thanks it works now!. I have one more question regarding virtual environment. If I use virtual environment then how can I use scikit, since if I follow the steps as mentioned above ,it installs the packages in /usr/local/Cellar/. Even though I activate virtual environment but brew install numpy

[Scikit-learn-general] Runtime warning scikit 0.15, warning for numpy

Hello, I had installed scikit-learn for Mac 10.9.2. since it showed dependencies, I used the wheel as mentioned in the website pip install -U numpy scipy scikit-learn , but when I import a cluster model it throws some warnings However if I use scikit-learn 0.14 then it does not give any excepti