rf_train.py 文件源码

def val_tune_rf(estimator,x_train,y_train,x_val,y_val,params):
    params_list = list(ParameterGrid(params))
    print params_list
    print y_val
    results = []
    for param in params_list:
        print '=========  ',param
        estimator.set_params(**param)
        estimator.fit(x_train,y_train)
        preds_prob = estimator.predict_proba(x_val)
        # print preds_prob[:,1]
        result = roc_auc_score(y_val,preds_prob[:,1])
        print 'roc_auc_score : %f'%result
        results.append((param,result))
    results.sort(key=lambda k: k[1])
    print results
    print results[-1]