[B! scikit-learn] mega-ne0221ã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

mega-ne0221 id:mega-ne0221

scikit-learnã«é–¢ã™ã‚‹mega-ne0221ã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (6)

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

${{author_name}}$
{{author_name}}{{created}}
{{ #comment }}{{ comment }}{{ /comment }}
- {{ label }}

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

scikit-learn ã«ä»˜å±žã—ã¦ã„ã‚‹ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆ
scikit-learn ã«ã¯ã€æ©Ÿæ¢°å¦ç¿’ã‚„ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°ã‚’ã™ãã«è©¦ã™ã“ã¨ãŒã§ãã‚‹ã‚ˆã†ã€å®Ÿé¨“ç”¨ãƒ‡ãƒ¼ã‚¿ãŒåŒæ¢±ã•ã‚Œã¦ã„ã¾ã™ã€‚ã“ã®ãƒšãƒ¼ã‚¸ã§ã¯ã€ã„ãã¤ã‹ã®ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆã«ã¤ã„ã¦ç´¹ä»‹ã—ã¾ã™ã€‚ Iris (ã‚¢ãƒ¤ãƒ¡ã®è¨ˆæ¸¬ãƒ‡ãƒ¼ã‚¿ã€é€šç§°ï¼šã‚¢ã‚¤ãƒªã‚¹) â€œsetosaâ€, â€œversicolorâ€, â€œvirginicaâ€ ã¨ã„ã† 3 ç¨®é¡žã®å“ç¨®ã®ã‚¢ãƒ¤ãƒ¡ã®ãŒãç‰‡ (Sepal)ã€èŠ±å¼ (Petal) ã®å¹…ãŠã‚ˆã³é•·ã•ã‚’è¨ˆæ¸¬ã—ãŸãƒ‡ãƒ¼ã‚¿ã§ã™ã€‚ ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆã®è©³ç´° ãƒ¬ã‚³ãƒ¼ãƒ‰æ•°
mega-ne0221 2017/01/19
sepal

ã‚ã¨ã§èªã‚€

scikit-learn

Python

ãƒ‡ãƒ¼ã‚¿

ã‚¢ãƒ¤ãƒ¡

ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°

æ©Ÿæ¢°å¦ç¿’
ãƒªãƒ³ã‚¯
3.6. scikit-learn: Python ã§ã®æ©Ÿæ¢°å¦ç¿’ â€” Scipy lecture notes
æ‰‹å§‹ã‚ã«ã„ãã¤ã‹ã®ãƒ‡ãƒ¼ã‚¿ã‚’è§¦ã£ã¦ã¿ã¾ã—ã‚‡ã†ã€‚ãƒ‡ãƒ¼ã‚¿ã¨ã—ã¦ Iris ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆã¨ã—ã¦çŸ¥ã‚‰ã‚Œã™ã€ã¨ã¦ã‚‚å˜ç´”ãªèŠ±ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚’ä½¿ã„ã¾ã—ã‚‡ã†ã€‚ 150 ã®ã‚¢ãƒ¤ãƒ¡ã®èŠ±ã®æ¸¬å®šå€¤ãŒã‚ã‚Šã¾ã™: sepal length, sepal width, petal length ãã—ã¦ petal width ã§ Iris setosa Iris versicolor Iris virginica ãã‚Œãžã‚Œã®å“ç¨®æ¯Žã«ã€‚ ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆã‚’ Python ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã¨ã—ã¦èªã¿è¾¼ã¿ã¾ã—ã‚‡ã†:
mega-ne0221 2017/01/19
sepal

ã‚ã¨ã§èªã‚€

Python

scikit-learn

ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆ

æ©Ÿæ¢°å¦ç¿’

ãƒ‡ãƒ¼ã‚¿
ãƒªãƒ³ã‚¯
scikit-learn ã§æ©Ÿæ¢°å¦ç¿’
scikit-learn (èªã¿æ–¹ã¯ã€Œã‚µã‚¤ã‚ãƒƒãƒˆãƒ»ãƒ©ãƒ¼ãƒ³ã€) ã¯ã€Python ã®æ©Ÿæ¢°å¦ç¿’ (Machine Learning; ãƒžã‚·ãƒ³ãƒ»ãƒ©ãƒ¼ãƒ‹ãƒ³ã‚°) ã®ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã§ã™ã€‚ scikit-learn ã¯ä»¥ä¸‹ã®ã‚ˆã†ãªç‰¹å¾´ãŒã‚ã‚Šã¾ã™ã€‚ NumPy, SciPy ã‚„ Matplotlib ã¨äº’æ›æ€§ã‚’æŒã¤ã‚ˆã†ã«é–‹ç™ºã•ã‚Œã¦ã„ã¾ã™ã€‚ä¾‹ãˆã°ã€NumPy ã§ä½œæˆã—ãŸè¡Œåˆ—ã‚’æ©Ÿæ¢°å¦ç¿’ã®å…¥åŠ›ãƒ‡ãƒ¼ã‚¿ã¨ã—ã¦æ‰±ã†ã“ã¨ãŒã§ãã¾ã™ã€‚ ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ (BSD ãƒ©ã‚¤ã‚»ãƒ³ã‚¹) ã§å…¬é–‹ã•ã‚Œã¦ãŠã‚Šã€ç„¡æ–™ã§åˆ©ç”¨ã§ãã‚‹ã ã‘ã§ãªãã€å•†ç”¨ã«ã‚‚åˆ©ç”¨å¯èƒ½ã§ã™ã€‚ ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã‚„å›žå¸°ã€åˆ†é¡žå™¨ã€æ¬¡å…ƒåœ§ç¸®ã€ãƒ‡ãƒ¼ã‚¿ã®å‰å‡¦ç†ã‚’ã¯ã˜ã‚ã¨ã™ã‚‹ã€æ©Ÿæ¢°å¦ç¿’ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã‚’å¹…åºƒãå®Ÿè£…ã—ã¦ã„ã¾ã™ã€‚ ã“ã®ã‚µã‚¤ãƒˆã§ã¯ã€ãƒ‡ãƒ¼ã‚¿ã‚’ç”¨ã„ã¦ã€ã„ãã¤ã‹ã®æ©Ÿæ¢°å¦ç¿’ã‚’ç”¨ã„ãŸãƒ‡ãƒ¼ã‚¿åˆ†æžã‚’å®Ÿè¡Œã™ã‚‹ãŸã‚ã®æ‰‹é †ã‚’ç´¹ä»‹ã—ã¾ã™ã€‚ scikit-learn ã§æ±ºå®šæœ¨åˆ†æž (Decision Tr
mega-ne0221 2016/12/15
Webãƒ‡ã‚¶ã‚¤ãƒ³

ã‚ã¨ã§èªã‚€

scikit-learn

ãƒ‡ãƒ¼ã‚¿

ã‚¯ãƒ©ã‚¹ã‚¿

python

machine learning

æ©Ÿæ¢°å¦ç¿’

Python

K-m

ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°
ãƒªãƒ³ã‚¯
scikit-learnã§æ©Ÿæ¢°å¦ç¿’ã‚’è©¦ã™ SVM - Qiita
ã“ã‚“ã«ã¡ã¯ã€‚åˆå¿ƒè€…ã§ã™ã€‚ ã‚ã‚‹ã‚µãƒ¼ãƒ“ã‚¹ï¼ˆå¿µå†™ã§ãã‚‹äººã¨ä½•ã‹å¿µå†™ã—ã¦ã»ã—ã„äººã®ãƒžãƒƒãƒãƒ³ã‚°ã‚µãƒ¼ãƒ“ã‚¹ã§ã™ï¼‰ã§æ©Ÿæ¢°å¦ç¿’ãŸã‚ãã†ã¨æ€ã£ã¦ã„ã¦ã€èª¿ã¹ã¦ã„ã‚‹æœ€ä¸ã§ã™ã€‚ å•é¡Œ è©¦ã—ã«ã€ã“ã‚Œã®1å•ç›®ã‚’è§£ãã‚ˆãƒ¼ã€‚ æ•™å¸«ã‚ã‚Šå¦ç¿’ã®å•é¡Œã§ã™ã€‚ä¸Šè¨˜ãƒšãƒ¼ã‚¸ã®å›žç”ä¾‹ã®ã‚ˆã†ã«ã€SVMã‚’ä½¿ã£ã¦ã¿ã¾ã™ã€‚ ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¯ã€scikit-learnã‚’ä½¿ã£ã¦ã¿ãŸã€‚ SVMä½¿ã„ãŸã„ã ã‘ãªã‚‰ã»ã‹ã«ã‚‚ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã‚ã‚‹ã¿ãŸã„ã ã‘ã©ã€scikit-learnã„ã„ã‚ˆ~çš„ãªã“ã¨ã‚’è¨€ã†äººãŒå¤šã„ã®ã§ä½¿ã£ã¦ã¿ã¾ã—ãŸã€‚ ã¨ã‚Šã‚ãˆãšã‚„ã£ã¦ã¿ã‚‹ # -*- coding: utf-8 -*- from sklearn.svm import LinearSVC import numpy as np # å¦ç¿’ãƒ‡ãƒ¼ã‚¿ data_training_tmp = np.loadtxt('CodeIQ_auth.txt', delimiter=' ') data_train
mega-ne0221 2016/12/15
ã‚ã¨ã§èªã‚€

ãƒ©ã‚¤ãƒ–ãƒ©ãƒª

data

scikit-learn

svm

python

æ©Ÿæ¢°å¦ç¿’

SVM

txt

ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°
ãƒªãƒ³ã‚¯
ã€ç‰¹åˆ¥é€£è¼‰ã€‘ ã•ãã€è‡ªç„¶è¨€èªžå‡¦ç†ã‚’å§‹ã‚ã‚ˆã†ï¼ï¼ˆæœ€çµ‚å›žï¼š æ©Ÿæ¢°å¦ç¿’ã«ã‚ˆã‚‹ãƒ†ã‚ã‚¹ãƒˆãƒžã‚¤ãƒ‹ãƒ³ã‚°ï¼‰
ã¿ãªã•ã¾ã“ã‚“ã«ã¡ã¯ã€‚ å‰å›žã®é€£è¼‰ ã€ç‰¹åˆ¥é€£è¼‰ã€‘ ã•ãã€è‡ªç„¶è¨€èªžå‡¦ç†ã‚’å§‹ã‚ã‚ˆã†ï¼ï¼ˆç¬¬2å›žï¼š å˜ç´”é›†è¨ˆã«ã‚ˆã‚‹ãƒ†ã‚ã‚¹ãƒˆãƒžã‚¤ãƒ‹ãƒ³ã‚°ï¼‰ ã§ã¯ TF-IDF ã‚’ç”¨ã„ã¦ Twitter Streaming API çµŒç”±ã§å–å¾—ã—ãŸæ—¥æœ¬èªž Tweet ãƒ‡ãƒ¼ã‚¿ã‹ã‚‰ã€ã‚ã‚‹æ—¥ã®ç‰¹å¾´èªžã‚’æŠ½å‡ºã™ã‚‹æ–¹æ³•ã‚’ç´¹ä»‹ã—ã¾ã—ãŸã€‚ ä»Šå›žã¯æ©Ÿæ¢°å¦ç¿’ã‚’ç”¨ã„ãŸãƒ†ã‚ã‚¹ãƒˆãƒžã‚¤ãƒ‹ãƒ³ã‚°ã‚’è¡Œã„ãŸã„ã¨æ€ã„ã¾ã™ã€‚æ©Ÿæ¢°å¦ç¿’ã¨ã¯ã€ŒçµŒé¨“ã«ã‚ˆã‚Šè‡ªå‹•çš„ã«æ”¹å–„ã—ã¦ã„ãã€ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ãƒ¼ãƒ—ãƒã‚°ãƒ©ãƒ ã®æ§‹ç¯‰æ–¹æ³•ã«é–¢ã‚ã‚‹åˆ†é‡Žã§ã™ã€‚ å…·ä½“çš„ã«ã¯ Python ã®æ©Ÿæ¢°å¦ç¿’ç”¨ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã‚ã‚‹ scikit-learn ã‚’ç”¨ã„ã¦ã€é›†ã‚ãŸ Tweet ãƒ‡ãƒ¼ã‚¿ã‚’ã€Œãƒã‚¸ãƒ†ã‚£ãƒ–ã€ã€ã€Œãƒã‚¬ãƒ†ã‚£ãƒ–ã€ãªã‚‚ã®ã«è‡ªå‹•ã§åˆ†é¡žã™ã‚‹æ–¹æ³•ã‚’ç´¹ä»‹ã—ã¾ã™ã€‚ å‡¦ç†ã®æµã‚Œä»Šå›žè¡Œã†å‡¦ç†ã¯æ¬¡ã®ã‚ˆã†ãªæµã‚Œã«ãªã‚Šã¾ã™ã€‚å¦ç¿’ç”¨ãƒ‡ãƒ¼ã‚¿ã®ä½œæˆãƒ‡ãƒ¼ã‚¿ã®å‰å‡¦ç†æ‰‹æ³•ã®é¸æŠžãƒ¢ãƒ‡ãƒ«ã®å¦ç¿’æœªçŸ¥è¦ç´ ã®åˆ†é¡žå®Ÿè¡Œç’°å¢ƒã¯å‰å›žã€å‰ã€…å›žã§ä½¿ç”¨ã—ãŸ A
mega-ne0221 2016/12/15
ã‚ã¨ã§èªã‚€

ãƒ†ã‚ã‚¹ãƒˆãƒžã‚¤ãƒ‹ãƒ³ã‚°

python

æ©Ÿæ¢°å¦ç¿’

è‡ªç„¶è¨€èªžå‡¦ç†

scikit-learn

svm
ãƒªãƒ³ã‚¯
scikit-learn ã‹ã‚‰å¦ã¶æ©Ÿæ¢°å¦ç¿’ã®æ‰‹æ³•ã®æ¦‚è¦ - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? å‰å›žã€æ ªå¼ã®æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã‚’åˆ†æžã™ã‚‹è©±ã§ã€å¾ŒåŠã«ã¡ã‚‡ã£ã¨ã ã‘æ©Ÿæ¢°å¦ç¿’ã®è©±ã‚’ã—ã¾ã—ãŸã€‚ä»Šæ—¥ã¯æ©Ÿæ¢°å¦ç¿’ãƒ©ã‚¤ãƒ–ãƒ©ãƒª scikit-learn ã«è§¦ã‚Œã¾ã™ã€‚ scikit-learn ã¨ã„ãˆã°ä»¥å‰ã«ã‚‚ç°¡å˜ãªã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã®ä¾‹ã‚’ã‚ã’ãŸã‚Šã€ã‚µãƒãƒ¼ãƒˆãƒ™ã‚¯ãƒˆãƒ«ãƒžã‚·ãƒ³ã‚„ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã§å•é¡Œã‚’è§£ãã€ TF-IDF ã‚’è¨ˆç®—ã™ã‚‹ã€å›žå¸°ãƒ¢ãƒ‡ãƒ«ã®å¯è¦–åŒ–ã€ DBSCAN ã«ã‚ˆã‚‹ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã¨ã„ã£ãŸã“ã¨ã‚’ã—ã¦ãã¾ã—ãŸãŒã€ã‚ã‚‰ãŸã‚ã¦ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã®æ©Ÿèƒ½ã‚’æ•´ç†ã—ã¾ã™ã€‚ æ©Ÿæ¢°å¦ç¿’ã¨è¨€ã†ã¨é›£ã—ã„æ•°å¦ã‚’é§†ä½¿ã™ã‚‹ã‚¤ãƒ¡ãƒ¼ã‚¸ãŒã¤ãã¾ã¨ã„ã¾ã™ãŒã€å®Œæˆåº¦ã®é«˜ã„ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã‚’ä½¿ãˆã°åˆ©ç”¨è€…ãŒæ©Ÿæ¢°å¦
mega-ne0221 2016/05/06
ã‚ã¨ã§èªã‚€

python

machinelearning

machine-learning

scikit-learn

æ©Ÿæ¢°å¦ç¿’
ãƒªãƒ³ã‚¯
1