Improvements on cmvfts and pwfts for multivariate forecasting

This commit is contained in:
Petrônio Cândido 2018-12-11 22:55:15 -02:00
parent 0d033c3ac2
commit 358a6ea287
2 changed files with 4 additions and 2 deletions

View File

@ -86,7 +86,7 @@ class ClusteredMVFTS(mvfts.MVFTS):
self.target_variable = var self.target_variable = var
self.cluster.change_target_variable(var) self.cluster.change_target_variable(var)
self.model.partitioner = self.cluster self.model.partitioner = self.cluster
self.reset_calculated_values() self.model.reset_calculated_values()
ret[var.name] = self.model.forecast(ndata, fuzzyfied=self.pre_fuzzyfy, **kwargs) ret[var.name] = self.model.forecast(ndata, fuzzyfied=self.pre_fuzzyfy, **kwargs)

View File

@ -45,4 +45,6 @@ ax[0][1].scatter(forecasts['x'].values,forecasts['y'].values)
ax[1][0].scatter(test['y'].values,test['x'].values) ax[1][0].scatter(test['y'].values,test['x'].values)
ax[1][0].scatter(forecasts['y'].values,forecasts['x'].values) ax[1][0].scatter(forecasts['y'].values,forecasts['x'].values)
ax[1][1].plot(test['y'].values) ax[1][1].plot(test['y'].values)
ax[1][1].plot(forecasts['y'].values) ax[1][1].plot(forecasts['y'].values)
print(forecasts)