These are chat archives for thunder-project/thunder
model.betasis very quick, and computing
model.score(regressors, imSeries)is now separate function which takes forever?
fitonly takes a
jointhe betas with the appropriate records in the Series
model, scores = LineareRegression().fit_and_score(X, y)
so, I have
Series mode: spark dtype: float64 shape: (41, 1024, 2048, 4)
and I call
betas.tolocal() to get a numpy array. For some reason, this operation takes forever. Any idea why?
BTW, when I call
algorithm = LinearRegression(fit_intercept=True) model, stats = algorithm.fit_and_score(regressors, imSeries)
it complains with
/usr/local/python-2.7.6/lib/python2.7/site-packages/scipy/linalg/basic.py:884: RuntimeWarning: internal gelsd driver lwork query error, required iwork dimension not returned. This is likely the result of LAPACK bug 0038, fixed in LAPACK 3.2.2 (released July 21, 2010). Falling back to 'gelss' driver.
scipyto the latest version last week by my request