0.0.2. Perhaps.

* where it started from

* initial work 1

* snowstorm

* holidays

* a sound like thunder

* you never know

* Witcher S1E1

I read quite a few of the books, new show looks surprisingly historically accurate in appearance... by movie standards.

* Witcher S1E3

* Christmas Eve

* Christmas

* Early Morning Fog

* Verily I say onto thee

* skiing

* but I am the Chosen One

* sorta works a bit

* ensemble of doom

* ensemble v 1

* nvidia graphics update, better save quick!

* single iteration functional

* take the keys and see what happens!

* cold winds blow

* frenetic sprint to a shifting shambles

* finally, regressing a bit

* ittle bitty changes

* really should have pulled first...

* It works. In an awkward sorta way

* 0.0.1, hopefully

* 0.0.2. For now.

Author: winedarksea

README.md

@@ -1,5 +1,5 @@
 # AutoTS
-Unstable prototype: version 0.0.1
+Unstable prototype: version 0.0.2
 ### Project CATS (Catlin Automated Time Series)
 (or maybe eventually: Clustered Automated Time Series)
 #### Model Selection for Multiple Time Series

autots/__init__.py

@@ -6,7 +6,8 @@
 from autots.datasets import load_toy_daily
 from autots.evaluator.auto_ts import AutoTS
 
-__version__ = '0.0.1'
+__version__ = '0.0.2'
+
 
 __all__ = ['load_toy_daily', 'AutoTS']
 

setup.py

@@ -1,7 +1,7 @@
 import setuptools
 
 required = [
-    "numpy", "pandas", "statsmodels", "sklearn>=0.20.0","holidays"
+    "numpy", "pandas", "statsmodels", "scikit-learn","holidays"
 ]
 
 extras = {
@@ -13,7 +13,7 @@
 
 setuptools.setup(
     name="AutoTS",
-    version="0.0.1",
+    version="0.0.2",
     author="Colin Catlin",
     author_email="colin.catlin@syllepsis.live",
     description="Automated Time Series Forecasting",