From e4ee163660a65dd184bfd47fe7df60daea3a0493 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Petr=C3=B4nio=20C=C3=A2ndido=20de=20Lima=20e=20Silva?= Date: Thu, 1 Nov 2018 11:31:28 -0300 Subject: [PATCH] Updating the links due to notebook refactoring --- docs/quickstart.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/quickstart.rst b/docs/quickstart.rst index 151b16d..6a4f02b 100644 --- a/docs/quickstart.rst +++ b/docs/quickstart.rst @@ -27,7 +27,7 @@ Fuzzy Time Series (FTS) are non parametric methods for time series forecasting b - which fuzzy membership function (on `pyFTS.common.Membership `_) - partition scheme (`GridPartitioner `_, `EntropyPartitioner `_, `FCMPartitioner `_, `CMeansPartitioner `_, `HuarngPartitioner `_) - Check out the jupyter notebook on `pyFTS/notebooks/Partitioners.ipynb `_ for sample codes. + Check out the jupyter notebook on `pyFTS/notebooks/Partitioners.ipynb `_ for sample codes. 3. **Data Fuzzyfication**: Each data point of the numerical time series *Y(t)* will be translated to a fuzzy representation (usually one or more fuzzy sets), and then a fuzzy time series *F(t)* is created. @@ -47,7 +47,7 @@ Fuzzy Time Series (FTS) are non parametric methods for time series forecasting b Usage examples -------------- -There is nothing better than good code examples to start. `Then check out the demo Jupyter Notebooks of the implemented method os pyFTS! `_. +There is nothing better than good code examples to start. `Then check out the demo Jupyter Notebooks of the implemented method os pyFTS! `_. A Google Colab example can also be found `here `_.