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  <h1>Source code for federatedml.tree.decision_tree</h1><div class="highlight"><pre>
<span></span><span class="ch">#!/usr/bin/env python    </span>
<span class="c1"># -*- coding: utf-8 -*- </span>

<span class="c1">#</span>
<span class="c1">#  Copyright 2019 The FATE Authors. All Rights Reserved.</span>
<span class="c1">#</span>
<span class="c1">#  Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);</span>
<span class="c1">#  you may not use this file except in compliance with the License.</span>
<span class="c1">#  You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1">#      http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1">#  Unless required by applicable law or agreed to in writing, software</span>
<span class="c1">#  distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1">#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1">#  See the License for the specific language governing permissions and</span>
<span class="c1">#  limitations under the License.</span>
<span class="c1">#</span>

<span class="c1"># =============================================================================</span>
<span class="c1"># DecisionTree Base Class</span>
<span class="c1"># =============================================================================</span>


<div class="viewcode-block" id="DecisionTree"><a class="viewcode-back" href="../../../federatedml.tree.html#federatedml.tree.decision_tree.DecisionTree">[docs]</a><span class="k">class</span> <span class="nc">DecisionTree</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">tree_param</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">criterion_method</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">criterion_method</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">criterion_params</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">criterion_params</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">max_depth</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">max_depth</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">min_sample_split</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">min_sample_split</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">min_impurity_split</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">min_impurity_split</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">min_leaf_node</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">min_leaf_node</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">max_split_nodes</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">max_split_nodes</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">feature_importance_type</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">feature_importance_type</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">n_iter_no_change</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">n_iter_no_change</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">tol</span> <span class="o">=</span> <span class="n">tree_param</span><span class="o">.</span><span class="n">tol</span>

<div class="viewcode-block" id="DecisionTree.fit"><a class="viewcode-back" href="../../../federatedml.tree.html#federatedml.tree.decision_tree.DecisionTree.fit">[docs]</a>    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">&quot;fit method should overload&quot;</span><span class="p">)</span></div>

<div class="viewcode-block" id="DecisionTree.predict"><a class="viewcode-back" href="../../../federatedml.tree.html#federatedml.tree.decision_tree.DecisionTree.predict">[docs]</a>    <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_inst</span><span class="p">):</span>
        <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">&quot;fit method should overload&quot;</span><span class="p">)</span></div></div>
</pre></div>

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