export PredictionSet

Author: thierrymoudiki

examples/mts_timeseries_xreg.py

@@ -85,7 +85,7 @@ def extract_month_year(df, date_column='date'):
 
 # Fit model
 model = ns.MTS(RidgeCV(alphas=10**np.linspace(-3, 3, 100)), 
-               replications=100,
+               replications=5,
                lags=25,
                type_pi="scp2-kde",
                kernel='gaussian',

nnetsauce/__init__.py

@@ -26,6 +26,7 @@
 from .neuralnet.neuralnetclassification import NeuralNetClassifier
 from .optimizers.optimizer import Optimizer
 from .predictioninterval import PredictionInterval
+from .predictionset import PredictionSet
 from .quantile.quantileregression import QuantileRegressor
 from .quantile.quantileclassification import QuantileClassifier
 from .randombag.randomBagClassifier import RandomBagClassifier
@@ -72,6 +73,7 @@
     "NeuralNetRegressor",
     "NeuralNetClassifier",
     "PredictionInterval",
+    "PredictionSet",
     "SimpleMultitaskClassifier",
     "Optimizer",
     "QuantileRegressor",

nnetsauce/mts/mts.py

@@ -1402,6 +1402,8 @@ def predict(self, h=5, level=95, quantiles=None, **kwargs):
 
             res = DescribeResult(self.mean_, self.lower_, self.upper_)
 
+            print("\n res", res)
+
             if self.xreg_ is not None:
                 if len(self.xreg_.shape) > 1:
                     res2 = mx.tuple_map(
@@ -1450,6 +1452,8 @@ def predict(self, h=5, level=95, quantiles=None, **kwargs):
 
             res = DescribeResult(self.mean_, self.lower_, self.upper_)
 
+            print("\n res", res)
+
             if self.xreg_ is not None:
                 if len(self.xreg_.shape) > 1:
                     res2 = mx.tuple_map(
@@ -1478,6 +1482,8 @@ def predict(self, h=5, level=95, quantiles=None, **kwargs):
 
             res = DescribeResult(self.mean_)
 
+            print("\n res", res)
+
             if self.xreg_ is not None:
                 if len(self.xreg_.shape) > 1:
                     res2 = mx.tuple_map(

setup.py

@@ -3,7 +3,7 @@
 from codecs import open
 from os import path
 
-__version__ = '0.43.0'
+__version__ = '0.44.0'
 
 # get the dependencies and installs
 here = path.abspath(path.dirname(__file__))