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  • pyFTS.common.transformations.roi
  • pyFTS.common.transformations.scale
  • pyFTS.common.transformations.smoothing
  • +
  • pyFTS.common.transformations.som
  • pyFTS.common.transformations.transformation
  • pyFTS.common.transformations.trend
  • pyFTS.common.tree
  • diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html index d94c8b4..2b634a9 100644 --- a/docs/build/html/genindex.html +++ b/docs/build/html/genindex.html @@ -206,6 +206,8 @@
  • (pyFTS.common.transformations.smoothing.ExponentialSmoothing method)
  • (pyFTS.common.transformations.smoothing.MovingAverage method) +
  • +
  • (pyFTS.common.transformations.som.SOMTransformation method)
  • (pyFTS.common.transformations.transformation.Transformation method)
  • @@ -1603,6 +1605,8 @@
  • pyFTS.common.transformations.scale
  • pyFTS.common.transformations.smoothing +
  • +
  • pyFTS.common.transformations.som
  • pyFTS.common.transformations.transformation
  • @@ -2290,6 +2294,13 @@ +
  • + pyFTS.common.transformations.som + +
  • @@ -3028,6 +3039,8 @@
  • save_dataframe_point() (in module pyFTS.benchmarks.Util)
  • save_dataframe_probabilistic() (in module pyFTS.benchmarks.Util) +
  • +
  • save_net() (pyFTS.common.transformations.som.SOMTransformation method)
  • Scale (class in pyFTS.common.transformations.scale)
  • @@ -3098,6 +3111,8 @@
  • shortname (pyFTS.common.fts.FTS attribute)
  • show_and_save_image() (in module pyFTS.common.Util) +
  • +
  • show_grid() (pyFTS.common.transformations.som.SOMTransformation method)
  • sigmf() (in module pyFTS.common.Membership)
  • @@ -3134,6 +3149,8 @@
  • sliding_window_benchmarks2() (in module pyFTS.benchmarks.benchmarks)
  • smape() (in module pyFTS.benchmarks.Measures) +
  • +
  • SOMTransformation (class in pyFTS.common.transformations.som)
  • SortedCollection (class in pyFTS.common.SortedCollection)
  • @@ -3187,6 +3204,8 @@
  • (pyFTS.common.fts.FTS method)
  • (pyFTS.common.transformations.normalization.Normalization method) +
  • +
  • (pyFTS.common.transformations.som.SOMTransformation method)
  • (pyFTS.common.transformations.trend.LinearTrend method)
  • diff --git a/docs/build/html/modules.html b/docs/build/html/modules.html index 6392f5a..12f7719 100644 --- a/docs/build/html/modules.html +++ b/docs/build/html/modules.html @@ -107,7 +107,7 @@
  • pyFTS.common.transformations.roi module
  • pyFTS.common.transformations.scale module
  • pyFTS.common.transformations.smoothing module
  • -
  • pyFTS.common.transformations.som module
  • +
  • pyFTS.common.transformations.som module
  • pyFTS.common.transformations.transformation module
  • pyFTS.common.transformations.trend module
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+ +     + pyFTS.common.transformations.som +     diff --git a/docs/build/html/pyFTS.common.transformations.html b/docs/build/html/pyFTS.common.transformations.html index f334fed..ad201fe 100644 --- a/docs/build/html/pyFTS.common.transformations.html +++ b/docs/build/html/pyFTS.common.transformations.html @@ -410,8 +410,51 @@ y(t) = ( y(t-1) * y’(t) ) + y(t-1)

    -
    -

    pyFTS.common.transformations.som module¶

    +
    +

    pyFTS.common.transformations.som module¶

    +

    Kohonen Self Organizing Maps for Fuzzy Time Series

    +
    +
    +class pyFTS.common.transformations.som.SOMTransformation(grid_dimension: Tuple, **kwargs)[source]¶
    +

    Bases: pyFTS.common.transformations.transformation.Transformation

    +
    +
    +apply(data: pandas.core.frame.DataFrame, param=None, **kwargs)[source]¶
    +

    Transform a M-dimensional dataset into a 3-dimensional dataset, where one dimension is the endogen variable +If endogen_variable = None, the last column will be the endogen_variable. +Args:

    +
    +

    data (pd.DataFrame): M-Dimensional dataset +endogen_variable (str): column of dataset +names (Tuple): names for new columns created by SOM Transformation. +param: +**kwargs: params of SOM’s train process

    +
    +

    percentage_train (float). Percentage of dataset that will be used for train SOM network. default: 0.7 +leaning_rate (float): leaning rate of SOM network. default: 0.01 +epochs: epochs of SOM network. default: 10000

    +
    +
    +

    Returns:

    +
    + +
    +
    +save_net(filename: str = 'SomNet trained')[source]¶
    +
    + +
    +
    +show_grid(graph_type: str = 'nodes_graph', **kwargs)[source]¶
    +
    + +
    +
    +train(data: pandas.core.frame.DataFrame, percentage_train: float = 0.7, leaning_rate: float = 0.01, epochs: int = 10000)[source]¶
    +
    + +
    +

    pyFTS.common.transformations.transformation module¶

    @@ -582,7 +625,7 @@ y(t) = y’(t) + (a*t+b)

  • pyFTS.common.transformations.roi module
  • pyFTS.common.transformations.scale module
  • pyFTS.common.transformations.smoothing module
  • -
  • pyFTS.common.transformations.som module
  • +
  • pyFTS.common.transformations.som module
  • pyFTS.common.transformations.transformation module
  • pyFTS.common.transformations.trend module
  • diff --git a/docs/build/html/pyFTS.html b/docs/build/html/pyFTS.html index 455d360..eb12838 100644 --- a/docs/build/html/pyFTS.html +++ b/docs/build/html/pyFTS.html @@ -108,7 +108,7 @@
  • pyFTS.common.transformations.roi module
  • pyFTS.common.transformations.scale module
  • pyFTS.common.transformations.smoothing module
  • -
  • pyFTS.common.transformations.som module
  • +
  • pyFTS.common.transformations.som module
  • pyFTS.common.transformations.transformation module
  • pyFTS.common.transformations.trend module
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- Fuzzy Time Series for Python","pyFTS","pyFTS package","pyFTS.benchmarks package","pyFTS.common package","pyFTS.common.transformations package","pyFTS.data package","pyFTS.distributed package","pyFTS.hyperparam package","pyFTS.models package","pyFTS.models.ensemble package","pyFTS.models.incremental package","pyFTS.models.multivariate package","pyFTS.models.nonstationary package","pyFTS.models.seasonal package","pyFTS.partitioners package","pyFTS.probabilistic package","pyFTS Quick Start"],titleterms:{"short":17,FTS:17,adapativeexpect:5,airpasseng:6,arima:3,artifici:6,benchmark:3,bitcoin:6,boxcox:5,bst:3,chaotic:6,chen:9,cheng:9,cmean:15,cmsft:14,cmvft:12,common:[4,5,6,12,13,14],composit:4,conf:2,content:[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],cvft:13,data:6,dataset:6,differenti:5,dispi:7,distribut:7,dowjon:6,enrol:6,ensembl:10,entropi:15,ethereum:6,eur:6,evolutionari:8,exampl:17,fcm:15,flr:[4,12],flrg:[4,12,13],fts:4,fuzzi:[0,17],fuzzyset:4,gaussianproc:3,gbp:6,gener:6,glass:6,granular:12,grid:[12,15],gridsearch:8,henon:6,hoft:9,honsft:13,how:[0,17],huarng:15,hwang:9,hyperparam:8,ift:9,increment:11,incrementalensembl:11,index:0,inmet:6,instal:17,ismailefendi:9,kde:16,knn:3,librari:0,logistic_map:6,lorentz:6,mackei:6,malaysia:6,measur:3,membership:4,model:[9,10,11,12,13,14],modul:[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],msft:14,multiseason:10,multivari:12,mvft:12,naiv:3,nasdaq:6,nonstationari:13,normal:5,nsft:13,packag:[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],parallel_util:15,partition:[12,13,14,15],perturb:13,probabilist:16,probabilitydistribut:16,pwft:9,pyft:[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17],python:0,quantreg:3,quick:17,refer:0,residualanalysi:3,roi:5,rossler:6,sadaei:9,scale:5,season:14,seasonalindex:14,seri:[0,6,17],sft:14,simpl:15,singleton:15,smooth:5,som:5,sonda:6,song:9,sortedcollect:4,spark:7,start:17,subclust:15,submodul:[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16],subpackag:[2,9],sunspot:6,synthet:6,taiex:6,test:3,time:[0,6,17],timevari:11,transform:5,tree:4,trend:5,tutori:17,usag:17,usd:6,util:[3,4,8,13,15],variabl:12,what:[0,17],wmvft:12}}) \ No newline at end of file diff --git a/pyFTS/common/Transformations.py b/pyFTS/common/Transformations.py index c911c1b..205251b 100644 --- a/pyFTS/common/Transformations.py +++ b/pyFTS/common/Transformations.py @@ -5,15 +5,15 @@ Common data transformation used on pre and post processing of the FTS import numpy as np import pandas as pd import math -#from pyFTS.common.transformations.transformation import Transformation -#from pyFTS.common.transformations.differential import Differential -#from pyFTS.common.transformations.scale import Scale -#from pyFTS.common.transformations.adaptiveexpectation import AdaptiveExpectation -#from pyFTS.common.transformations.boxcox import BoxCox -#from pyFTS.common.transformations.roi import ROI -#from pyFTS.common.transformations.trend import LinearTrend -#from pyFTS.common.transformations.som import SOMTransformation -#from pyFTS.common.transformations.normalization import Normalization +from pyFTS.common.transformations.transformation import Transformation +from pyFTS.common.transformations.differential import Differential +from pyFTS.common.transformations.scale import Scale +from pyFTS.common.transformations.adaptiveexpectation import AdaptiveExpectation +from pyFTS.common.transformations.boxcox import BoxCox +from pyFTS.common.transformations.roi import ROI +from pyFTS.common.transformations.trend import LinearTrend +from pyFTS.common.transformations.som import SOMTransformation +from pyFTS.common.transformations.normalization import Normalization

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