July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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128
4
章
NumPy
の基礎：配列とベクトル演算
array([[-1.6914, 4.38 , 0.1757, 0.4075, -0.7838],
[ 0. , -2.6436, 0.1939, -3.072 , -1.0702],
[ 0. , 0. , -0.8138, 1.5414, 0.6155],
[ 0. , 0. , 0. , -2.6445, -2.1669],
[ 0. , 0. , 0. , 0. , 0.0002]])
X.T.dot(X)
という式は、
X
とその転置行列である
X.T
との内積を計算しています。
利用頻度が高い行列計算関数を表4-7に示します。
表4-7 よく用いられるnumpy.linalg関数
関数 説明
diag
正方行列の対角要素、あるいは非対角要素を
1
次元配列として返す。
1
次元配列に対しては、その要
素を対角要素に配置した対角行列（残りの成分を
0
で埋めた正方行列）を返す。
dot
2
つの行列の内積を計算する。
trace
対角要素の総和を計算する。
det
行列式を計算する。
eig
正方行列に対して固有値および固有ベクトルを計算する。
inv
正方行列に対して逆行列を計算する。
pinv
ムーア−ペンローズの擬似逆行列を計算する。
qr
QR
分解を計算する。
svd
特異値分解（
singular value decomposition, SVD
）を計算する。
solve
正方行列
A
に対して線形方程式
Ax=b
を
x
について解く。
lstsq Ax=b
に対して最小二乗法による近似を求め
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