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                <div class="box">
    <div class="inner-text">サポートベクターマシン(英: support vector machine, SVM)は、教師あり学習を用いるパターン認識モデルの一つである。分類や回帰へ適用できる。1963年に Vladimir N. Vapnik, Alexey Ya. Chervonenkis が線形サポートベクターマシンを発表し[1]、1992年に Bernhard E. Boser, Isabelle M. Guyon, Vladimir N. Vapnik が非線形へと拡張した。<br>サポートベクターマシンは、現在知られている手法の中でも認識性能が優れた学習モデルの一つである。サポートベクターマシンが優れた認識性能を発揮することができる理由は、未学習データに対して高い識別性能を得るための工夫があるためである。


                .box {
  position: relative;
  height: 60px;
  width: 400px;
  padding: 10px;
  background-color: whitesmoke;
  border: 0;
  border-radius: 10px;
  overflow-y: hidden;
  font-size: 20px;

.inner-text {
  height: 80px;
  white-space: nowrap;
  overflow-x: scroll;