階層クラスタリング(cluster.hierarchy)、ベクトル量子化 / K 平均法(cluster.vq)
constants
物理数学定数
fftpack
フーリエ変換
integrate
積分
interpolate
補間(リニア、キュービックなど)
io
データの入出力
linalg
BLASとLAPACKライブラリを用いた線形代数ルーチン
maxentropy
エントロピー分布
ndimage
n次元画像パッケージ
odr
直交距離回帰
optimize
最適化
signal
信号処理
sparse
疎行列
spatial
空間データ構造とアルゴリズム
special
ベッセル関数、ヤコビアンなどの特殊関数
stats
統計
本書で主に扱うパッケージは、
scipy.stats
、
scipy.interpolate
、
scipy.cluster
、
scipy.signal
です。後ほど、
stats
の特徴について簡単な説明を行います。その他については、
必要なときに改めて説明を行うものとします。
1.5
はじめての(簡単な)機械学習アプリケーション
それでは、実際に手を動かしながら、機械学習のアプリケーションを作ることにしましょう。ここで
は、Web関連のベンチャー企業である「MLAAS
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