Julia doesn't allow overloading field access for types, so you have to use this workaround in pycall -> hmmmodel[:fit](df[:abc])
On Thursday, September 25, 2014 3:22:16 PM UTC-4, Arshak Navruzyan wrote: > > I am trying to use a sklearn model in Julia. The first part works ok and > I get back the model object but when I try to fit the model, I get an error > > @pyimport sklearn.hmm as hmm > > hmmmodel = hmm.GaussianHMM(3, "full") > > PyObject GaussianHMM(algorithm='viterbi', covariance_type='full', > covars_prior=0.01, > covars_weight=1, > init_params='abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ', > means_prior=None, means_weight=0, n_components=3, n_iter=10, > params='abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ', > random_state=None, startprob=None, startprob_prior=None, thresh=0.01, > transmat=None, transmat_prior=None) > > > hmmmodel.fit(df[:abc]) > > > type PyObject has no field fit > while loading In[275], in expression starting on line 1 > >
