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Merge pull request #60 from yuta-nakahara/hotfix-metatree
Hotfix metatree
2 parents 868a592 + dffd081 commit 7a76f24

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‎README.md

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@@ -137,7 +137,7 @@ Plain text
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```
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Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,''
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,''
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[Online] https://github.com/yuta-nakahara/BayesML
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```
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@@ -148,7 +148,7 @@ BibTeX
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author = {Nakahara Yuta and Ichijo Naoki and Shimada Koshi and
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Iikubo Yuji and Saito Shota and Kazama Koki and
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Matsushima Toshiyasu and {BayesML Developers}},
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title = {BayesML 0.2.2},
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title = {BayesML 0.2.3},
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howpublished = {\url{https://github.com/yuta-nakahara/BayesML}},
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year = {2022}
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}

‎README_jp.md

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@@ -134,7 +134,7 @@ BayesMLへのコントリビューションを考えてくださってありが
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```
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Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,''
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,''
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[Online] https://github.com/yuta-nakahara/BayesML
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```
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@@ -145,7 +145,7 @@ BibTeX
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author = {Nakahara Yuta and Ichijo Naoki and Shimada Koshi and
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Iikubo Yuji and Saito Shota and Kazama Koki and
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Matsushima Toshiyasu and {BayesML Developers}},
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title = {BayesML 0.2.2},
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title = {BayesML 0.2.3},
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howpublished = {\url{https://github.com/yuta-nakahara/BayesML}},
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year = {2022}
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}

‎bayesml/metatree/_metatree.py

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@@ -2416,13 +2416,17 @@ def make_prediction(self,loss="squared"):
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The predicted value under the given loss function.
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"""
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if loss == "squared":
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tmp_pred_vec = np.empty(len(self.hn_metatree_list))
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if self.SubModel is categorical:
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tmp_pred_vec = np.empty([len(self.hn_metatree_list),self.sub_constants['c_degree']])
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else:
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tmp_pred_vec = np.empty(len(self.hn_metatree_list))
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for i,metatree in enumerate(self.hn_metatree_list):
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tmp_pred_vec[i] = self._make_prediction_recursion_squared(metatree)
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return self.hn_metatree_prob_vec @ tmp_pred_vec
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elif loss == "0-1":
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if self.SubModel in CLF_MODELS:
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tmp_pred_dist_vec = np.empty([len(self.hn_metatree_list),2])
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degree = 2 if self.SubModel is bernoulli else self.sub_constants['c_degree']
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tmp_pred_dist_vec = np.empty([len(self.hn_metatree_list),degree])
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for i,metatree in enumerate(self.hn_metatree_list):
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tmp_pred_dist_vec[i] = self._make_prediction_recursion_kl(metatree)
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return np.argmax(self.hn_metatree_prob_vec @ tmp_pred_dist_vec)
@@ -2431,7 +2435,8 @@ def make_prediction(self,loss="squared"):
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+"only when self.SubModel is bernoulli or categorical."))
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elif loss == "KL":
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if self.SubModel in CLF_MODELS:
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tmp_pred_dist_vec = np.empty([len(self.hn_metatree_list),2])
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degree = 2 if self.SubModel is bernoulli else self.sub_constants['c_degree']
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tmp_pred_dist_vec = np.empty([len(self.hn_metatree_list),degree])
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for i,metatree in enumerate(self.hn_metatree_list):
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tmp_pred_dist_vec[i] = self._make_prediction_recursion_kl(metatree)
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return self.hn_metatree_prob_vec @ tmp_pred_dist_vec

‎doc/developers.rst

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@@ -59,7 +59,7 @@ Plain text
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.. code-block::
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Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,''
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,''
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[Online] https://github.com/yuta-nakahara/BayesML
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@@ -71,7 +71,7 @@ BibTeX
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author = {Nakahara Yuta and Ichijo Naoki and Shimada Koshi and
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Iikubo Yuji and Saito Shota and Kazama Koki and
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Matsushima Toshiyasu and {BayesML Developers}},
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title = {BayesML 0.2.2},
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title = {BayesML 0.2.3},
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howpublished = {\url{https://github.com/yuta-nakahara/BayesML}},
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year = {2022}
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}

‎doc/index.rst

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.. code-block::
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Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,''
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,''
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[Online] https://github.com/yuta-nakahara/BayesML
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@@ -162,7 +162,7 @@ BibTeX
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author = {Nakahara Yuta and Ichijo Naoki and Shimada Koshi and
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Iikubo Yuji and Saito Shota and Kazama Koki and
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Matsushima Toshiyasu and {BayesML Developers}},
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title = {BayesML 0.2.2},
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title = {BayesML 0.2.3},
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howpublished = {\url{https://github.com/yuta-nakahara/BayesML}},
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year = {2022}
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}

‎docs/developers.html

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@@ -380,7 +380,7 @@ <h3>Citation<a class="headerlink" href="#citation" title="Permalink to this head
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<p>When you use BayesML for your academic work, please provide the following bibliographic reference.</p>
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<p>Plain text</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,&#39;&#39;
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,&#39;&#39;
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[Online] https://github.com/yuta-nakahara/BayesML
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</pre></div>
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</div>
@@ -389,7 +389,7 @@ <h3>Citation<a class="headerlink" href="#citation" title="Permalink to this head
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<span class="na">author</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Nakahara Yuta and Ichijo Naoki and Shimada Koshi and</span>
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<span class="s"> Iikubo Yuji and Saito Shota and Kazama Koki and</span>
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<span class="s"> Matsushima Toshiyasu and {BayesML Developers}}</span><span class="p">,</span><span class="w"></span>
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<span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{BayesML 0.2.2}</span><span class="p">,</span><span class="w"></span>
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<span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{BayesML 0.2.3}</span><span class="p">,</span><span class="w"></span>
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<span class="na">howpublished</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{\url{https://github.com/yuta-nakahara/BayesML}}</span><span class="p">,</span><span class="w"></span>
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<span class="na">year</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{2022}</span><span class="w"></span>
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<span class="p">}</span><span class="w"></span>

‎docs/index.html

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@@ -480,7 +480,7 @@ <h2>Citation<a class="headerlink" href="#citation" title="Permalink to this head
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<p>When you use BayesML for your academic work, please provide the following bibliographic reference.</p>
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<p>Plain text</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>Y. Nakahara, N. Ichijo, K. Shimada, Y. Iikubo,
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.2,&#39;&#39;
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S. Saito, K. Kazama, T. Matsushima, BayesML Developers, ``BayesML 0.2.3,&#39;&#39;
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[Online] https://github.com/yuta-nakahara/BayesML
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</pre></div>
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</div>
@@ -489,7 +489,7 @@ <h2>Citation<a class="headerlink" href="#citation" title="Permalink to this head
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<span class="na">author</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{Nakahara Yuta and Ichijo Naoki and Shimada Koshi and</span>
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<span class="s"> Iikubo Yuji and Saito Shota and Kazama Koki and</span>
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<span class="s"> Matsushima Toshiyasu and {BayesML Developers}}</span><span class="p">,</span><span class="w"></span>
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<span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{BayesML 0.2.2}</span><span class="p">,</span><span class="w"></span>
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<span class="na">title</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{BayesML 0.2.3}</span><span class="p">,</span><span class="w"></span>
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<span class="na">howpublished</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{\url{https://github.com/yuta-nakahara/BayesML}}</span><span class="p">,</span><span class="w"></span>
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<span class="na">year</span><span class="w"> </span><span class="p">=</span><span class="w"> </span><span class="s">{2022}</span><span class="w"></span>
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<span class="p">}</span><span class="w"></span>

‎setup.py

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setup(
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name='bayesml',
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version='0.2.2',
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version='0.2.3',
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packages=find_packages(),
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author='Yuta Nakahara et al.',
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author_email='yuta.nakahara@aoni.waseda.jp',

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