我的模型准确率为什么那么低，是哪有问题吗，随机森林不是准确率很高吗
输出结果0.37010975031949667 9不应该啊import pandas as pd #导入数据集
url=r"C:\Users\zmj佳佳佳\Desktop\第六步离散化测试.csv"
df = pd.read_csv(url, header = None,low_memory=False)#将数据集分为训练集和测试集
df.columns=["grade","dti","delinq_2yrs","earliest_cr_line","fico_range_low","inq_last_6mths",
"mths_since_last_delinq","pub_rec","revol_bal","revol_util","mths_since_last_major_derog",
"tot_cur_bal","open_acc_6m","open_il_12m","open_il_24m","mths_since_rcnt_il","open_rv_12m",
"open_rv_24m","max_bal_bc","all_util","inq_last_12m","acc_open_past_24mths","avg_cur_bal",
"bc_open_to_buy","mo_sin_old_il_acct","mo_sin_old_rev_tl_op","mo_sin_rcnt_rev_tl_op","mo_sin_rcnt_tl",
"mort_acc","mths_since_recent_bc_dlq","mths_since_recent_inq","mths_since_recent_revol_delinq",
"num_accts_ever_120_pd","num_actv_bc_tl","num_actv_rev_tl","num_bc_sats","num_bc_tl",
"num_rev_accts","num_rev_tl_bal_gt_0","num_tl_90g_dpd_24m","num_tl_op_past_12m","pct_tl_nvr_dlq",
"pub_rec_bankruptcies"]
#将数据集分为训练集和测试集
from sklearn.model_selection import train_test_split
from sklearn.model_selection import GridSearchCV
from sklearn.ensemble import RandomForestClassifier
x, y = df.iloc[:, 1:].values, df.iloc[:, 0].values
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.3, random_state = 0)
feat_labels = df.columns
#param={"n_estimators":,"max_depth":}
#网格搜索与交叉验证
#gc=GridSearchCV(forest,param_grid=param,cv=3)
#gc.fit(x_train,y_train)
#print("准确率：",gc.score(x_test,y_test))
#print("查看选择的参数模型：",gc.best_params_)
#n_estimators的学习曲线
from sklearn.model_selection import cross_val_score
import matplotlib.pyplot as plt
superpa = []
for i in range(0,10):
forest = RandomForestClassifier(n_estimators=i+1,n_jobs=-1)
rfc_s = cross_val_score(forest,x,y,cv=2).mean()
superpa.append(rfc_s)
print(max(superpa),superpa.index(max(superpa)))
plt.figure(figsize=)
plt.plot(range(1,11),superpa)
plt.show()
有没有人可以帮忙指导下吗
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