di_values = di_values.dropna()
f = spy.stats.genextreme.fit(di_values)
cutoff = spy.stats.genextreme.ppf(
- self.freqai_info.get("outlier_threshold"), *f
+ self.freqai_info.get("outlier_threshold", 0.999), *f
)
dk.data["DI_value_mean"] = pred_df_full["DI_values"].mean()
di_values = di_values.dropna()
f = spy.stats.genextreme.fit(di_values)
cutoff = spy.stats.genextreme.ppf(
- self.freqai_info.get("outlier_threshold"), *f
+ self.freqai_info.get("outlier_threshold", 0.999), *f
)
dk.data["DI_value_mean"] = pred_df_full["DI_values"].mean()
di_values = di_values.dropna()
f = spy.stats.genextreme.fit(di_values)
cutoff = spy.stats.genextreme.ppf(
- self.freqai_info.get("outlier_threshold"), *f
+ self.freqai_info.get("outlier_threshold", 0.999), *f
)
dk.data["DI_value_mean"] = pred_df_full["DI_values"].mean()