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realstealthninja
@@ -4,7 +4,7 @@
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<title>TheAlgorithms/C++: machine_learning/adaline_learning.cpp File Reference</title>
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@@ -60,7 +60,7 @@ window.MathJax = {
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@@ -153,6 +153,8 @@ Include dependency graph for adaline_learning.cpp:</div>
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Classes</h2></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></td></tr>
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<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/df2/classadaline.html">adaline</a></td></tr>
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<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="namespaces" name="namespaces"></a>
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Namespaces</h2></td></tr>
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@@ -263,9 +265,9 @@ Variables</h2></td></tr>
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<div class="fragment"><div class="line"><span class="lineno"> 224</span> {</div>
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<div class="line"><span class="lineno"> 225</span> <a class="code hl_class" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
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<div class="line"><span class="lineno"> 226</span> </div>
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<div class="line"><span class="lineno"> 227</span> <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a> = 10; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 227</span> <span class="keyword">const</span> <span class="keywordtype">int</span> N = 10; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 228</span> </div>
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<div class="line"><span class="lineno"> 229</span> std::array<std::vector<double>, <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>> X = {</div>
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<div class="line"><span class="lineno"> 229</span> std::array<std::vector<double>, N> X = {</div>
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<div class="line"><span class="lineno"> 230</span> std::vector<double>({0, 1}), std::vector<double>({1, -2}),</div>
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<div class="line"><span class="lineno"> 231</span> std::vector<double>({2, 3}), std::vector<double>({3, -1}),</div>
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<div class="line"><span class="lineno"> 232</span> std::vector<double>({4, 1}), std::vector<double>({6, -5}),</div>
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@@ -277,7 +279,7 @@ Variables</h2></td></tr>
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<div class="line"><span class="lineno"> 238</span> std::cout << <span class="stringliteral">"------- Test 1 -------"</span> << std::endl;</div>
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<div class="line"><span class="lineno"> 239</span> std::cout << <span class="stringliteral">"Model before fit: "</span> << ada << std::endl;</div>
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<div class="line"><span class="lineno"> 240</span> </div>
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<div class="line"><span class="lineno"> 241</span> ada.fit<<a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>>(X, y);</div>
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<div class="line"><span class="lineno"> 241</span> ada.fit<N>(X, y);</div>
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<div class="line"><span class="lineno"> 242</span> std::cout << <span class="stringliteral">"Model after fit: "</span> << ada << std::endl;</div>
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<div class="line"><span class="lineno"> 243</span> </div>
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<div class="line"><span class="lineno"> 244</span> <span class="keywordtype">int</span> predict = ada.predict({5, -3});</div>
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@@ -291,7 +293,6 @@ Variables</h2></td></tr>
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<div class="line"><span class="lineno"> 252</span> std::cout << <span class="stringliteral">" ...passed"</span> << std::endl;</div>
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<div class="line"><span class="lineno"> 253</span>}</div>
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<div class="ttc" id="aclassmachine__learning_1_1adaline_html"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html">machine_learning::adaline</a></div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00046">adaline_learning.cpp:46</a></div></div>
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<div class="ttc" id="asparse__table_8cpp_html_a10f3ffb3f6f7e1b83d556b9c8de89a5d"><div class="ttname"><a href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">data_structures::sparse_table::N</a></div><div class="ttdeci">constexpr uint32_t N</div><div class="ttdoc">A struct to represent sparse table for min() as their invariant function, for the given array A....</div><div class="ttdef"><b>Definition</b> <a href="../../d8/dab/sparse__table_8cpp_source.html#l00048">sparse_table.cpp:48</a></div></div>
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@@ -320,16 +321,16 @@ Variables</h2></td></tr>
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<div class="fragment"><div class="line"><span class="lineno"> 262</span> {</div>
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<div class="line"><span class="lineno"> 263</span> <a class="code hl_class" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(2, eta); <span class="comment">// 2 features</span></div>
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<div class="line"><span class="lineno"> 264</span> </div>
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<div class="line"><span class="lineno"> 265</span> <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a> = 50; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 265</span> <span class="keyword">const</span> <span class="keywordtype">int</span> N = 50; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 266</span> </div>
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<div class="line"><span class="lineno"> 267</span> std::array<std::vector<double>, <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>> X;</div>
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<div class="line"><span class="lineno"> 267</span> std::array<std::vector<double>, N> X;</div>
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<div class="line"><span class="lineno"> 268</span> std::array<int, N> Y{}; <span class="comment">// corresponding y-values</span></div>
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<div class="line"><span class="lineno"> 269</span> </div>
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<div class="line"><span class="lineno"> 270</span> <span class="comment">// generate sample points in the interval</span></div>
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<div class="line"><span class="lineno"> 271</span> <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
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<div class="line"><span class="lineno"> 272</span> <span class="keywordtype">int</span> range = 500; <span class="comment">// sample points full-range</span></div>
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<div class="line"><span class="lineno"> 273</span> <span class="keywordtype">int</span> range2 = range >> 1; <span class="comment">// sample points half-range</span></div>
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<div class="line"><span class="lineno"> 274</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>; i++) {</div>
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<div class="line"><span class="lineno"> 274</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) {</div>
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<div class="line"><span class="lineno"> 275</span> <span class="keywordtype">double</span> x0 = (<span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(std::rand() % range) - range2) / 100.f;</div>
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<div class="line"><span class="lineno"> 276</span> <span class="keywordtype">double</span> x1 = (<span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(std::rand() % range) - range2) / 100.f;</div>
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<div class="line"><span class="lineno"> 277</span> X[i] = std::vector<double>({x0, x1});</div>
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@@ -385,16 +386,16 @@ Variables</h2></td></tr>
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<div class="fragment"><div class="line"><span class="lineno"> 313</span> {</div>
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<div class="line"><span class="lineno"> 314</span> <a class="code hl_class" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> ada(6, eta); <span class="comment">// 2 features</span></div>
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<div class="line"><span class="lineno"> 315</span> </div>
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<div class="line"><span class="lineno"> 316</span> <span class="keyword">const</span> <span class="keywordtype">int</span> <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a> = 100; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 316</span> <span class="keyword">const</span> <span class="keywordtype">int</span> N = 100; <span class="comment">// number of sample points</span></div>
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<div class="line"><span class="lineno"> 317</span> </div>
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<div class="line"><span class="lineno"> 318</span> std::array<std::vector<double>, <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>> X;</div>
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<div class="line"><span class="lineno"> 318</span> std::array<std::vector<double>, N> X;</div>
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<div class="line"><span class="lineno"> 319</span> std::array<int, N> Y{}; <span class="comment">// corresponding y-values</span></div>
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<div class="line"><span class="lineno"> 320</span> </div>
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<div class="line"><span class="lineno"> 321</span> <span class="comment">// generate sample points in the interval</span></div>
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<div class="line"><span class="lineno"> 322</span> <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
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<div class="line"><span class="lineno"> 323</span> <span class="keywordtype">int</span> range = 200; <span class="comment">// sample points full-range</span></div>
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<div class="line"><span class="lineno"> 324</span> <span class="keywordtype">int</span> range2 = range >> 1; <span class="comment">// sample points half-range</span></div>
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<div class="line"><span class="lineno"> 325</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>; i++) {</div>
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<div class="line"><span class="lineno"> 325</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) {</div>
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<div class="line"><span class="lineno"> 326</span> <span class="keywordtype">double</span> x0 = (<span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(std::rand() % range) - range2) / 100.f;</div>
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<div class="line"><span class="lineno"> 327</span> <span class="keywordtype">double</span> x1 = (<span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(std::rand() % range) - range2) / 100.f;</div>
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<div class="line"><span class="lineno"> 328</span> <span class="keywordtype">double</span> x2 = (<span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(std::rand() % range) - range2) / 100.f;</div>
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@@ -433,7 +434,7 @@ Variables</h2></td></tr>
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<li class="navelem"><a class="el" href="../../dir_3343723ae086de42ee4ca9774da3a13f.html">machine_learning</a></li><li class="navelem"><a class="el" href="../../d5/db0/adaline__learning_8cpp.html">adaline_learning.cpp</a></li>
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