<spanid="pyfts-models-song-module"></span><h2>pyFTS.models.song module<aclass="headerlink"href="#module-pyFTS.models.song"title="Permalink to this headline">¶</a></h2>
<p>First Order Traditional Fuzzy Time Series method by Song & Chissom (1993)</p>
<olclass="upperalpha simple"start="17">
<li>Song and B. S. Chissom, “Fuzzy time series and its models,” Fuzzy Sets Syst., vol. 54, no. 3, pp. 269–277, 1993.</li>
</ol>
<dlclass="class">
<dtid="pyFTS.models.song.ConventionalFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.song.</code><codeclass="descname">ConventionalFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/song.html#ConventionalFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.song.ConventionalFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">flr_membership_matrix</code><spanclass="sig-paren">(</span><em>flr</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/song.html#ConventionalFTS.flr_membership_matrix"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.song.ConventionalFTS.flr_membership_matrix"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/song.html#ConventionalFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.song.ConventionalFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">operation_matrix</code><spanclass="sig-paren">(</span><em>flrs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/song.html#ConventionalFTS.operation_matrix"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.song.ConventionalFTS.operation_matrix"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.song.ConventionalFTS.train">
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/song.html#ConventionalFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.song.ConventionalFTS.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-chen-module"></span><h2>pyFTS.models.chen module<aclass="headerlink"href="#module-pyFTS.models.chen"title="Permalink to this headline">¶</a></h2>
<p>First Order Conventional Fuzzy Time Series by Chen (1996)</p>
<p>S.-M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, pp. 311–319, 1996.</p>
<dlclass="class">
<dtid="pyFTS.models.chen.ConventionalFLRG">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.chen.</code><codeclass="descname">ConventionalFLRG</code><spanclass="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_key</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFLRG.get_key"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFLRG.get_key"title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a unique identifier for this FLRG</p>
</dd></dl>
</dd></dl>
<dlclass="class">
<dtid="pyFTS.models.chen.ConventionalFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.chen.</code><codeclass="descname">ConventionalFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_flrg</code><spanclass="sig-paren">(</span><em>flrs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFTS.generate_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFTS.generate_flrg"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.chen.ConventionalFTS.train">
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/chen.html#ConventionalFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.chen.ConventionalFTS.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-yu-module"></span><h2>pyFTS.models.yu module<aclass="headerlink"href="#module-pyFTS.models.yu"title="Permalink to this headline">¶</a></h2>
<p>First Order Weighted Fuzzy Time Series by Yu(2005)</p>
<p>H.-K. Yu, “Weighted fuzzy time series models for TAIEX forecasting,”
Phys. A Stat. Mech. its Appl., vol. 349, no. 3, pp. 609–624, 2005.</p>
<dlclass="class">
<dtid="pyFTS.models.yu.WeightedFLRG">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.yu.</code><codeclass="descname">WeightedFLRG</code><spanclass="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFLRG"title="Permalink to this definition">¶</a></dt>
<p>First Order Weighted Fuzzy Logical Relationship Group</p>
<dlclass="method">
<dtid="pyFTS.models.yu.WeightedFLRG.append_rhs">
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.yu.WeightedFLRG.weights">
<codeclass="descname">weights</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFLRG.weights"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFLRG.weights"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dlclass="class">
<dtid="pyFTS.models.yu.WeightedFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.yu.</code><codeclass="descname">WeightedFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_FLRG</code><spanclass="sig-paren">(</span><em>flrs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFTS.generate_FLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFTS.generate_FLRG"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.yu.WeightedFTS.train">
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/yu.html#WeightedFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.yu.WeightedFTS.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-cheng-module"></span><h2>pyFTS.models.cheng module<aclass="headerlink"href="#module-pyFTS.models.cheng"title="Permalink to this headline">¶</a></h2>
<p>Trend Weighted Fuzzy Time Series by Cheng, Chen and Wu (2009)</p>
<p>C.-H. Cheng, Y.-S. Chen, and Y.-L. Wu, “Forecasting innovation diffusion of products using trend-weighted fuzzy time-series model,”
Expert Syst. Appl., vol. 36, no. 2, pp. 1826–1832, 2009.</p>
<dlclass="class">
<dtid="pyFTS.models.cheng.TrendWeightedFLRG">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.cheng.</code><codeclass="descname">TrendWeightedFLRG</code><spanclass="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.cheng.TrendWeightedFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">weights</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/cheng.html#TrendWeightedFLRG.weights"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.cheng.TrendWeightedFLRG.weights"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dlclass="class">
<dtid="pyFTS.models.cheng.TrendWeightedFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.cheng.</code><codeclass="descname">TrendWeightedFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.cheng.TrendWeightedFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_FLRG</code><spanclass="sig-paren">(</span><em>flrs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/cheng.html#TrendWeightedFTS.generate_FLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-hofts-module"></span><h2>pyFTS.models.hofts module<aclass="headerlink"href="#module-pyFTS.models.hofts"title="Permalink to this headline">¶</a></h2>
<p>High Order FTS</p>
<p>Severiano, S. A. Jr; Silva, P. C. L.; Sadaei, H. J.; Guimarães, F. G. Very Short-term Solar Forecasting
using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DOI10.1109/FUZZ-IEEE.2017.8015732</p>
<dlclass="class">
<dtid="pyFTS.models.hofts.HighOrderFLRG">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.hofts.</code><codeclass="descname">HighOrderFLRG</code><spanclass="sig-paren">(</span><em>order</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_lhs</code><spanclass="sig-paren">(</span><em>c</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_lhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFLRG.append_lhs"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dlclass="class">
<dtid="pyFTS.models.hofts.HighOrderFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.hofts.</code><codeclass="descname">HighOrderFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">configure_lags</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS.configure_lags"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS.configure_lags"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.hofts.HighOrderFTS.forecast">
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_flrg</code><spanclass="sig-paren">(</span><em>data</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_lhs_flrg</code><spanclass="sig-paren">(</span><em>sample</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.hofts.HighOrderFTS.train">
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hofts.html#HighOrderFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hofts.HighOrderFTS.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-hwang-module"></span><h2>pyFTS.models.hwang module<aclass="headerlink"href="#module-pyFTS.models.hwang"title="Permalink to this headline">¶</a></h2>
<p>High Order Fuzzy Time Series by Hwang, Chen and Lee (1998)</p>
<p>Jeng-Ren Hwang, Shyi-Ming Chen, and Chia-Hoang Lee, “Handling forecasting problems using fuzzy time series,”
Fuzzy Sets Syst., no. 100, pp. 217–228, 1998.</p>
<dlclass="class">
<dtid="pyFTS.models.hwang.HighOrderFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.hwang.</code><codeclass="descname">HighOrderFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hwang.html#HighOrderFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hwang.HighOrderFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">configure_lags</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hwang.html#HighOrderFTS.configure_lags"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hwang.HighOrderFTS.configure_lags"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.hwang.HighOrderFTS.forecast">
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hwang.html#HighOrderFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hwang.HighOrderFTS.forecast"title="Permalink to this definition">¶</a></dt>
<li><strong>data</strong>– time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong>– model specific parameters</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">a list with the forecasted values</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dlclass="method">
<dtid="pyFTS.models.hwang.HighOrderFTS.train">
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/hwang.html#HighOrderFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.hwang.HighOrderFTS.train"title="Permalink to this definition">¶</a></dt>
<trclass="field-odd field"><thclass="field-name">Parameters:</th><tdclass="field-body"><ulclass="first last simple">
<li><strong>data</strong>– training time series data</li>
<li><strong>kwargs</strong>– Method specific parameters</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<divclass="section"id="module-pyFTS.models.ifts">
<spanid="pyfts-models-ifts-module"></span><h2>pyFTS.models.ifts module<aclass="headerlink"href="#module-pyFTS.models.ifts"title="Permalink to this headline">¶</a></h2>
<p>High Order Interval Fuzzy Time Series</p>
<p>SILVA, Petrônio CL; SADAEI, Hossein Javedani; GUIMARÃES, Frederico Gadelha. Interval Forecasting with Fuzzy Time Series.
In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016. p. 1-8.</p>
<dlclass="class">
<dtid="pyFTS.models.ifts.IntervalFTS">
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.ifts.</code><codeclass="descname">IntervalFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ifts.html#IntervalFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ifts.IntervalFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast_interval</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ifts.html#IntervalFTS.forecast_interval"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ifts.IntervalFTS.forecast_interval"title="Permalink to this definition">¶</a></dt>
<li><strong>data</strong>– time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong>– model specific parameters</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">a list with the forecasted intervals</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dlclass="method">
<dtid="pyFTS.models.ifts.IntervalFTS.get_lower">
<codeclass="descname">get_lower</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_lower"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ifts.IntervalFTS.get_lower"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_sequence_membership</code><spanclass="sig-paren">(</span><em>data</em>, <em>fuzzySets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_sequence_membership"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ifts.IntervalFTS.get_sequence_membership"title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="pyFTS.models.ifts.IntervalFTS.get_upper">
<codeclass="descname">get_upper</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ifts.html#IntervalFTS.get_upper"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ifts.IntervalFTS.get_upper"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-ismailefendi-module"></span><h2>pyFTS.models.ismailefendi module<aclass="headerlink"href="#module-pyFTS.models.ismailefendi"title="Permalink to this headline">¶</a></h2>
<p>First Order Improved Weighted Fuzzy Time Series by Efendi, Ismail and Deris (2013)</p>
<p>R. Efendi, Z. Ismail, and M. M. Deris, “Improved weight Fuzzy Time Series as used in the exchange rates forecasting of
US Dollar to Ringgit Malaysia,” Int. J. Comput. Intell. Appl., vol. 12, no. 1, p. 1350005, 2013.</p>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.ismailefendi.</code><codeclass="descname">ImprovedWeightedFLRG</code><spanclass="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">weights</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFLRG.weights"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights"title="Permalink to this definition">¶</a></dt>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.ismailefendi.</code><codeclass="descname">ImprovedWeightedFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_flrg</code><spanclass="sig-paren">(</span><em>flrs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.generate_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/ismailefendi.html#ImprovedWeightedFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-pwfts-module"></span><h2>pyFTS.models.pwfts module<aclass="headerlink"href="#module-pyFTS.models.pwfts"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.pwfts.</code><codeclass="descname">ProbabilisticWeightedFLRG</code><spanclass="sig-paren">(</span><em>order</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_lower</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_lower"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower"title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<codeclass="descname">get_membership</code><spanclass="sig-paren">(</span><em>data</em>, <em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_membership"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership"title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the membership value of the FLRG for the input data</p>
<codeclass="descname">get_midpoint</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_midpoint"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint"title="Permalink to this definition">¶</a></dt>
<dd><p>Return the expectation of the PWFLRG, the weighted sum</p>
<codeclass="descname">get_upper</code><spanclass="sig-paren">(</span><em>sets</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.get_upper"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper"title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<codeclass="descname">lhs_conditional_probability</code><spanclass="sig-paren">(</span><em>x</em>, <em>sets</em>, <em>norm</em>, <em>uod</em>, <em>nbins</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.lhs_conditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">partition_function</code><spanclass="sig-paren">(</span><em>sets</em>, <em>uod</em>, <em>nbins=100</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.partition_function"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">rhs_conditional_probability</code><spanclass="sig-paren">(</span><em>x</em>, <em>sets</em>, <em>uod</em>, <em>nbins</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_conditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">rhs_unconditional_probability</code><spanclass="sig-paren">(</span><em>c</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFLRG.rhs_unconditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability"title="Permalink to this definition">¶</a></dt>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.pwfts.</code><codeclass="descname">ProbabilisticWeightedFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">add_new_PWFLGR</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.add_new_PWFLGR"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">flrg_lhs_conditional_probability</code><spanclass="sig-paren">(</span><em>x</em>, <em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_conditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">flrg_lhs_unconditional_probability</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">flrg_rhs_conditional_probability</code><spanclass="sig-paren">(</span><em>x</em>, <em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.flrg_rhs_conditional_probability"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast_ahead</code><spanclass="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast_ahead_distribution</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>steps</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_distribution"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution"title="Permalink to this definition">¶</a></dt>
<li><strong>data</strong>– time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>steps</strong>– the number of steps ahead to forecast</li>
<li><strong>kwargs</strong>– model specific parameters</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">a list with the forecasted Probability Distributions</p>
<codeclass="descname">forecast_ahead_interval</code><spanclass="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_ahead_interval"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_interval"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast_distribution</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_distribution"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution"title="Permalink to this definition">¶</a></dt>
<li><strong>data</strong>– time series data with the minimal length equal to the max_lag of the model</li>
<li><strong>kwargs</strong>– model specific parameters</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">a list with the forecasted Probability Distributions</p>
<codeclass="descname">forecast_interval</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.forecast_interval"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_flrg</code><spanclass="sig-paren">(</span><em>data</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_lhs_flrg</code><spanclass="sig-paren">(</span><em>sample</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.generate_lhs_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_lower</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_lower"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_midpoint</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_midpoint"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_upper</code><spanclass="sig-paren">(</span><em>flrg</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.get_upper"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">interval_heuristic</code><spanclass="sig-paren">(</span><em>sample</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_heuristic"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">interval_quantile</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>alpha</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.interval_quantile"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">point_expected_value</code><spanclass="sig-paren">(</span><em>sample</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_expected_value"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">point_heuristic</code><spanclass="sig-paren">(</span><em>sample</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.point_heuristic"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.train"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">update_model</code><spanclass="sig-paren">(</span><em>data</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#ProbabilisticWeightedFTS.update_model"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.models.pwfts.</code><codeclass="descname">visualize_distributions</code><spanclass="sig-paren">(</span><em>model</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/pwfts.html#visualize_distributions"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.pwfts.visualize_distributions"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-models-sadaei-module"></span><h2>pyFTS.models.sadaei module<aclass="headerlink"href="#module-pyFTS.models.sadaei"title="Permalink to this headline">¶</a></h2>
<p>First Order Exponentialy Weighted Fuzzy Time Series by Sadaei et al. (2013)</p>
<p>H. J. Sadaei, R. Enayatifar, A. H. Abdullah, and A. Gani, “Short-term load forecasting using a hybrid model with a
refined exponentially weighted fuzzy time series and an improved harmony search,” Int. J. Electr. Power Energy Syst., vol. 62, no. from 2005, pp. 118–129, 2014.</p>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.sadaei.</code><codeclass="descname">ExponentialyWeightedFLRG</code><spanclass="sig-paren">(</span><em>LHS</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">append_rhs</code><spanclass="sig-paren">(</span><em>c</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.append_rhs"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">weights</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFLRG.weights"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights"title="Permalink to this definition">¶</a></dt>
<emclass="property">class </em><codeclass="descclassname">pyFTS.models.sadaei.</code><codeclass="descname">ExponentialyWeightedFTS</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFTS"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">forecast</code><spanclass="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.forecast"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">generate_flrg</code><spanclass="sig-paren">(</span><em>flrs</em>, <em>c</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.generate_flrg"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">train</code><spanclass="sig-paren">(</span><em>data</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/models/sadaei.html#ExponentialyWeightedFTS.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.models.sadaei.ExponentialyWeightedFTS.train"title="Permalink to this definition">¶</a></dt>
