Commit bf44f3b8 authored by ZHENQIN WU's avatar ZHENQIN WU
Browse files

update

parent 54efe778

deepchem/hyper/gaussian_process.py

+1 −1
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@@ -34,7 +34,7 @@ class GaussianProcessHyperparamOpt(HyperparamOpt): 
                            'bypass_dropouts', 'n_pair_feat', 'fit_transformers',

                            'min_child_weight', 'max_delta_step','subsample',

                            'colsample_bylevel', 'colsample_bytree', 'reg_alpha', 

                            'reg_lambda', 'scale_pos_weight', 'base_score'

                            'reg_lambda', 'scale_pos_weight', 'base_score', 'T', 'M'

                        ],

                        logdir=None,

                        log_file='GPhypersearch.log'):

deepchem/molnet/check_availability.py

+1 −0
Original line number Diff line number Diff line
@@ -163,6 +163,7 @@ CheckFeaturizer = { 
    ('pdbbind', 'tf_regression'): ['grid', 2052],

    ('pdbbind', 'rf_regression'): ['grid', 2052],

    ('pdbbind', 'krr'): ['grid', 2052],

    ('pdbbind', 'graphconvreg'): ['GraphConv', 75],

    ('qm7', 'tf_regression'): ['ECFP', 1024],

    ('qm7', 'rf_regression'): ['ECFP', 1024],

    ('qm7', 'krr'): ['ECFP', 1024],

deepchem/molnet/preset_hyper_parameters.py

+3 −3
Original line number Diff line number Diff line
@@ -154,9 +154,9 @@ hps['weave_regression'] = { 
}

hps['ani'] = {

    'batch_size': 32,

    'nb_epoch': 50,

    'learning_rate': 0.001,

    'layer_structures': [128, 128, 64],

    'nb_epoch': 100,

    'learning_rate': 0.00005,

    'layer_structures': [20, 10, 10],

    'seed': 123

}

hps['mpnn'] = {

examples/lipodag_regression.pkl

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(dp0

S'learning_rate'

p1

F0.0007668313439288658

sS'batch_size'

p2

I36

sS'n_graph_feat'

p3

I17

sS'seed'

p4

I123

sS'default_max_atoms'

p5

I74

sS'nb_epoch'

p6

I100

s.
 
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