in python i am trying to debug this error for a while now cansomeone help with debug 4944841

In PYTHON, I am trying to debug this error for a while now. Cansomeone help with debugging this? I got this code from this websitehttp://www.semspirit.com/artificial-intelligence/machine-learning/classification/classifier-evaluation/classifier-evaluation-with-cap-curve-in-python/ import matplotlib.pyplot as plt

from scipy import integrate #calculus integration def capcurve(y_values, y_preds_proba):

num_pos_obs = np.sum(y_values)

num_count = len(y_values)

rate_pos_obs = float(num_pos_obs) / float(num_count)

ideal = pd.DataFrame({‘x’:[0,rate_pos_obs,1],’y’:[0,1,1]})

xx = np.arange(num_count) / float(num_count – 1) y_cap = np.c_[y_values,y_preds_proba]

y_cap_df_s = pd.DataFrame(data=y_cap)

y_cap_df_s = y_cap_df_s.sort_values([1],ascending=False).reset_index(‘index’, drop=True)

  

print(y_cap_df_s.head(20)) yy = np.cumsum(y_cap_df_s[0]) / float(num_pos_obs)

yy = np.append([0], yy[0:num_count-1]) #add the first curve point(0,0) : for xx=0 we have yy=0 percent = 0.5

row_index = np.trunc(num_count * percent) val_y1 = yy[row_index]

val_y2 = yy[row_index+1]

if val_y1 == val_y2:

val = val_y1*1.0

else:

val_x1 = xx[row_index]

val_x2 = xx[row_index+1]

val = val_y1 + ((val_x2 – percent)/(val_x2 – val_x1))*(val_y2 -val_y1) sigma_ideal = 1 * xx[num_pos_obs – 1 ] / 2 + (xx[num_count – 1]- xx[num_pos_obs]) * 1

sigma_model = integrate.simps(yy,xx)

sigma_random = integrate.simps(xx,xx) ar_value = (sigma_model – sigma_random) / (sigma_ideal -sigma_random)

#ar_label = ‘ar value = %s’ % ar_value fig, ax = plt.subplots(nrows = 1, ncols = 1)

ax.plot(ideal[‘x’],ideal[‘y’], color=’grey’, label=’PerfectModel’)

ax.plot(xx,yy, color=’red’, label=’User Model’)

#ax.scatter(xx,yy, color=’red’)

ax.plot(xx,xx, color=’blue’, label=’Random Model’)

ax.plot([percent, percent], [0.0, val], color=’green’,linestyle=’–‘, linewidth=1)

ax.plot([0, percent], [val, val], color=’green’, linestyle=’–‘,linewidth=1, label=str(val*100)+’% of positive obs at’+str(percent*100)+’%’) plt.xlim(0, 1.02)

plt.ylim(0, 1.25)

plt.title(“CAP Curve – a_r value =”+str(ar_value))

plt.xlabel(‘% of the data’)

plt.ylabel(‘% of positive obs’)

plt.legend()

plt.show() ——————————————————————————– y_probablity =classifier.predict_proba(X_test)

capcurve(y_test, y_probablity[:,1]) ———————————————————————————- KeyError Traceback (most recent call last) in () 1 y_probablity =classifier.predict_proba(X_test)—-> 2 capcurve(y_test, y_probablity[:,1]) in capcurve(y_values, y_preds_proba) 11 y_cap = np.c_[y_values,y_preds_proba] 12 y_cap_df_s = pd.DataFrame(data=y_cap)—> 13 y_cap_df_s = y_cap_df_s.sort_values([1], ascending=False).reset_index(‘index’, drop=True) 14 15 print(y_cap_df_s.head(20))C:ANACONDAlibsite-packagespandascoreframe.py in reset_index(self, level, drop, inplace, col_level, col_fill) 4096 if not isinstance(level, (tuple, list)): 4097 level = [level]-> 4098 level = [self.index._get_level_number(lev) for lev in level] 4099 if isinstance(self.index, MultiIndex): 4100 if len(level) (.0) 4096 if not isinstance(level, (tuple, list)): 4097 level = [level]-> 4098 level = [self.index._get_level_number(lev) for lev in level] 4099 if isinstance(self.index, MultiIndex): 4100 if len(level) < self.index.nlevels:C:ANACONDAlibsite-packagespandascoreindexesbase.py in _get_level_number(self, level) 1944 1945 def _get_level_number(self, level):-> 1946 self._validate_index_level(level) 1947 return 0 1948 C:ANACONDAlibsite-packagespandascoreindexesbase.py in _validate_index_level(self, level) 1941 elif level != self.name: 1942 raise KeyError(‘Level %s must be same as name (%s)’ %-> 1943 (level, self.name)) 1944 1945 def _get_level_number(self, level):KeyError: ‘Level index must be same as name (None)’ . . .