索引

A

abstract class aggregation apply_over_axes

arange argmax argmin array

B

basinhopping Brent method

broadcastable broadcasting, [1] brute

C

class BaseBinaryNaiveBayes LogisticRegression NaiveBayes1, [1] NaiveBayes2

clip

D

dot	dtype, [1]

E

e empty

empty_like equal

F

floor_divide

frompyfunc

G

genfromtxt, [1]

I

identity

ipython ix_

L

log	logical_and logistic regression

M

matmul

minimize, [1], [2] minimize_scalar

N

naive Bayes multinomial ndarray, [1] astype dtype, [1] ndim, [1] shape, [1] view newaxis non-linear optimization np.apply_over_axes() (組み込み関数) np.arange() (組み込み関数) np.argmax() (組み込み関数) np.argmin() (組み込み関数) np.array() (組み込み関数) np.dot() (組み込み関数) np.dtype (組み込みクラス)

np.empty() (組み込み関数) np.empty_like() (組み込み関数) np.frompyfunc() (組み込み関数) np.genfromtxt() (組み込み関数) np.identity() (組み込み関数) np.ndarray (組み込みクラス) np.newaxis np.ones() (組み込み関数) np.ones_like() (組み込み関数) np.piecewise() (組み込み関数) np.reshape() (組み込み関数) np.select() (組み込み関数) np.sum() (組み込み関数) np.swapaxes() (組み込み関数) np.where() (組み込み関数) np.zeros() (組み込み関数) np.zeros_like() (組み込み関数)

O

ones ones_like

optimization, [1] OptimizeResult

P

pi

piecewise

R

reshape

S

sample lr.py lr1.py lr2.py lr3.py nbayes1.py nbayes1b.py nbayes2.py run_lr.py run_nbayes1.py run_nbayes1b.py run_nbayes2.py vote_filled.tsv

scikit-learn, [1] select seterr sigmoid function slice sp.constants sp.optimize.minimize() (組み込み関数) sp.optimize.minimize_scalar() (組み込み関数) sp.optimize.OptimizeResult (組み込みクラス) staticmethod structured array, [1], [2] sum swapaxes

T

timeit

transpose true_divide

U

ufunc

universal function, [1]

V

vectorize

W

where

Z

zeros

zeros_like