请问大家这串SHAP图的代码怎么用在多分类问题上？
def ABS_SHAP(df_shap,df):
#import matplotlib as plt

Make a copy of the input data

shap_v = pd.DataFrame(df_shap)
feature_list = df.columns
shap_v.columns = feature_list
df_v = df.copy().reset_index().drop('index',axis=1)

Determine the correlation in order to plot with different colors

corr_list = list()
for i in feature_list:
b = np.corrcoef(shap_v[i],df_v[i])[1][0]
corr_list.append(b)
corr_df = pd.concat([pd.Series(feature_list),pd.Series(corr_list)],axis=1).fillna(0)

Make a data frame. Column 1 is the feature, and Column 2 is the correlation coefficient

corr_df.columns = ['Variable','Corr']
corr_df['Sign'] = np.where(corr_df['Corr']>0,'red','blue')

Plot it

shap_abs = np.abs(shap_v)
k=pd.DataFrame(shap_abs.mean()).reset_index()
k.columns = ['Variable','SHAP_abs']
k2 = k.merge(corr_df,left_on = 'Variable',right_on='Variable',how='inner')
k2 = k2.sort_values(by='SHAP_abs',ascending = True)
colorlist = k2['Sign']
ax = k2.plot.barh

怎么了，出现什么问题