And for it toneverwarning about thenum_boost_roundkeyword argument having a different value than one passed throughparams, since "pass inparamsto override other configuration" is the approach we promote as many other places as possible in the library. So: # no warninglgb.train(params={"n_ite...
My wide guess is that most of our estimators in scikit-learn expect a single sample even at transform. I don't see a specific check in the estimator_check. @mlondschien Could you motivate in which case having an empty array is useful. My takes here would be that considering a Pipeline...
sample_weight : numpy array类型,形状为[n_samples]每个样本的权重. get_params(deep=True) Get parameters for this estimator...A constant model that always predicts the expecte...
sample_weight : numpy array类型,形状为[n_samples]每个样本的权重. get_params(deep=True) Get parameters for this estimator...A constant model that always predicts the expected value of y, disregarding the input features, would...‘sparse_cg’ uses the conjugate gradient solver ...