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class="sidebar secondary"><h3><a href="#top"><span class="inner">Public Vars</span></a></h3><ul><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-accuracy"><div class="inner"><span>accuracy</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-comp-metric"><div class="inner"><span>comp-metric</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-custom-metric"><div class="inner"><span>custom-metric</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-f1"><div class="inner"><span>f1</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-get"><div class="inner"><span>get</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-get-and-reset"><div class="inner"><span>get-and-reset</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-mae"><div class="inner"><span>mae</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-mse"><div class="inner"><span>mse</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-perplexity"><div class="inner"><span>perplexity</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-reset"><div class="inner"><span>reset</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-rmse"><div class="inner"><span>rmse</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-top-k-accuracy"><div class="inner"><span>top-k-accuracy</span></div></a></li><li class="depth-1"><a href="org.apache.clojure-mxnet.eval-metric.html#var-update"><div class="inner"><span>update</span></div></a></li></ul></div><div class="namespace-docs" id="content"><h1 class="anchor" id="top">org.apache.clojure-mxnet.eval-metric</h1><div class="doc"><pre class="plaintext"></pre></div><div class="public anchor" id="var-accuracy"><h3>accuracy</h3><div class="usage"><code>(accuracy)</code></div><div class="doc"><pre class="plaintext">Basic Accuracy Metric |
| </pre></div></div><div class="public anchor" id="var-comp-metric"><h3>comp-metric</h3><div class="usage"><code>(comp-metric metrics)</code></div><div class="doc"><pre class="plaintext">Create a metric instance composed out of several metrics |
| </pre></div></div><div class="public anchor" id="var-custom-metric"><h3>custom-metric</h3><h4 class="type">macro</h4><div class="usage"><code>(custom-metric f-eval mname)</code></div><div class="doc"><pre class="plaintext">Custom evaluation metric that takes a NDArray function. |
| - f-eval Customized evaluation function that takes two ndarrays and returns a number |
| function must be in the form of (fn [] ) clojure style |
| - mname The name of the metric</pre></div></div><div class="public anchor" id="var-f1"><h3>f1</h3><div class="usage"><code>(f1)</code></div><div class="doc"><pre class="plaintext">Calculate the F1 score of a binary classification problem. |
| </pre></div></div><div class="public anchor" id="var-get"><h3>get</h3><div class="usage"><code>(get metric)</code></div><div class="doc"><pre class="plaintext">Get the values of the metric in as a map of {name value} pairs |
| </pre></div></div><div class="public anchor" id="var-get-and-reset"><h3>get-and-reset</h3><div class="usage"><code>(get-and-reset metric)</code></div><div class="doc"><pre class="plaintext">Get the values and then reset the metric |
| </pre></div></div><div class="public anchor" id="var-mae"><h3>mae</h3><div class="usage"><code>(mae)</code></div><div class="doc"><pre class="plaintext">Calculate Mean Absolute Error loss |
| </pre></div></div><div class="public anchor" id="var-mse"><h3>mse</h3><div class="usage"><code>(mse)</code></div><div class="doc"><pre class="plaintext">Calculate Mean Squared Error loss |
| </pre></div></div><div class="public anchor" id="var-perplexity"><h3>perplexity</h3><div class="usage"><code>(perplexity {:keys [ignore-label axis], :as opts, :or {axis -1}})</code><code>(perplexity)</code></div><div class="doc"><pre class="plaintext">Calculate perplexity |
| - opts |
| :ignore-label Index of invalid label to ignore when counting. Usually should be -1. Include |
| all entries if None. |
| :axis The axis from prediction that was used to |
| compute softmax. Default is -1 which means use the last axis.</pre></div></div><div class="public anchor" id="var-reset"><h3>reset</h3><div class="usage"><code>(reset metric)</code></div><div class="doc"><pre class="plaintext">clear the internal statistics to an initial state |
| </pre></div></div><div class="public anchor" id="var-rmse"><h3>rmse</h3><div class="usage"><code>(rmse)</code></div><div class="doc"><pre class="plaintext">Calculate Root Mean Squred Error loss |
| </pre></div></div><div class="public anchor" id="var-top-k-accuracy"><h3>top-k-accuracy</h3><div class="usage"><code>(top-k-accuracy top-k)</code></div><div class="doc"><pre class="plaintext">Calculate to k predications accuracy |
| - top-k number of predicts (int)</pre></div></div><div class="public anchor" id="var-update"><h3>update</h3><div class="usage"><code>(update metric labels preds)</code></div><div class="doc"><pre class="plaintext">Update the internal evaluation |
| </pre></div></div></div></body></html> |
