def get_default_model(self):
    p = {}
    p['model'] = self.model_name
    p['train_grid'] = 'NONE'
    p['type_ml'] = 'classification'
    p['n_jobs'] = 8
    p['params'] = {}
    p['params']['tree_size'] = 4
    p['params']['sample_fract'] = 'default'
    p['params']['max_rules'] = 2000
    p['params']['memory_par'] = 0.01
    p['params']['rfmode'] = 'classify'
    p['params']['lin_trim_quantile'] = 0.025
    p['params']['lin_standardise'] = True
    p['params']['exp_rand_tree_size'] = True
    p['params_grid'] = {}
    return p
def get_default_model(self):
    p = {}
    p['model'] = self.model_name
    p['train_grid'] = 'NONE'
    p['type_ml'] = 'classification'
    p['n_jobs'] = 8
    p['params'] = {}
    p['params']['tree_size'] = 4
    p['params']['sample_fract'] = 'default'
    p['params']['max_rules'] = 2000
    p['params']['memory_par'] = 0.01
    p['params']['rfmode'] = 'classify'
    p['params']['lin_trim_quantile'] = 0.025
    p['params']['lin_standardise'] = True
    p['params']['exp_rand_tree_size'] = True
    p['params_grid'] = {}
    return p