{"id":808,"date":"2023-03-11T14:02:06","date_gmt":"2023-04-19T21:52:16","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/index.php\/2023\/11\/30\/python%e3%81%aescikit-learn%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%abnote-the-given-phrase-is-already-in-english-so-it-cannot-be-paraphrased-into-japanese-however-if-you-ar\/"},"modified":"2025-08-01T02:38:40","modified_gmt":"2025-07-31T17:38:40","slug":"python%e3%81%aescikit-learn%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%abnote-the-given-phrase-is-already-in-english-so-it-cannot-be-paraphrased-into-japanese-however-if-you-ar","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/python%e3%81%aescikit-learn%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%abnote-the-given-phrase-is-already-in-english-so-it-cannot-be-paraphrased-into-japanese-however-if-you-ar\/","title":{"rendered":"Python\u306eSciKit Learn\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb(Note: The given phrase is already in English, so it cannot be paraphrased into Japanese. However, if you are looking for a translation into Japanese, the provided phrase is already a suitable option.)"},"content":{"rendered":"

Scikit Learn\u3092\u65e5\u672c\u8a9e\u3067\u8868\u73fe\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308a\u307e\u3059\uff1a
\n\u30b5\u30a4\u30ad\u30c3\u30c8\u30fb\u30e9\u30fc\u30f3<\/h2>\n
\"python<\/div>\n

Python\u306eScikit-learn<\/h2>\n

Scikit\u306f\u3001\u307b\u3068\u3093\u3069\u304cPython\u3067\u66f8\u304b\u308c\u3066\u304a\u308a\u3001\u4e00\u90e8\u306e\u30b3\u30a2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3055\u3089\u306a\u308b\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u5411\u4e0a\u306e\u305f\u3081\u306bCython\u3067\u66f8\u304b\u308c\u3066\u3044\u307e\u3059\u3002Scikit-learn\u306f\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u304c\u3001\u30c7\u30fc\u30bf\u306e\u8aad\u307f\u53d6\u308a\u3084\u64cd\u4f5c\u3001\u8981\u7d04\u306b\u306f\u4ed6\u306e\u76ee\u7684\u306b\u7279\u5316\u3057\u305f\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306e\u4f7f\u7528\u304c\u63a8\u5968\u3055\u308c\u307e\u3059\u3002Scikit\u306f\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u3067\u3042\u308a\u3001BSD\u30e9\u30a4\u30bb\u30f3\u30b9\u3067\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n

Scikit Learn\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/h3>\n

Scikit\u3092\u4f7f\u7528\u3059\u308b\u306b\u306f\u3001Python 2.7\u307e\u305f\u306f\u305d\u308c\u4ee5\u4e0a\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306e\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u306b\u3001NumPY\uff081.8.2\u4ee5\u4e0a\uff09\u304a\u3088\u3073SciPY\uff080.13.3\u4ee5\u4e0a\uff09\u30d1\u30c3\u30b1\u30fc\u30b8\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u5834\u5408\u3001\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3092\u9032\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002pip\u3092\u4f7f\u7528\u3057\u3066\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5834\u5408\u306f\u3001\u30bf\u30fc\u30df\u30ca\u30eb\u3067\u6b21\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n

pip install scikit-learn\r\n<\/code><\/pre>\n
\u3082\u3057conda\u304c\u597d\u304d\u306a\u3089\u3001\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306b\u3082conda\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
conda install scikit-learn\r\n<\/code><\/pre>\n
Scikit-Learn\u3092\u4f7f\u7528\u3059\u308b<\/h2>\n
\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u304c\u5b8c\u4e86\u3057\u305f\u3089\u3001scikit-learn\u3092\u7c21\u5358\u306bPython\u30b3\u30fc\u30c9\u3067\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002\u6b21\u306e\u3088\u3046\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u3060\u3051\u3067\u3059\u3002<\/p>\n
import sklearn\r\n<\/code><\/pre>\n
scikit-learn\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u8fbc\u307f<\/h3>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u904a\u3073\u59cb\u3081\u307e\u3057\u3087\u3046\u3002\u7c21\u5358\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u3042\u308b\u300c\u30a2\u30a4\u30ea\u30b9\u300d\u3092\u8aad\u307f\u8fbc\u307f\u307e\u3057\u3087\u3046\u3002\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u82b1\u306b\u95a2\u3059\u308b150\u306e\u89b3\u5bdf\u7d50\u679c\u3092\u542b\u3093\u3067\u304a\u308a\u3001\u82b1\u306e\u3055\u307e\u3056\u307e\u306a\u6e2c\u5b9a\u5024\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002scikit-learn\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u8fbc\u307f\u65b9\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
# Import scikit learn\r\nfrom sklearn import datasets\r\n# Load data\r\niris= datasets.load_iris()\r\n# Print shape of data to confirm data is loaded\r\nprint(iris.data.shape)\r\n<\/code><\/pre>\n
\"python<\/div>\n
Scikit Learn\u306eSVM – \u5b66\u7fd2\u3068\u4e88\u6e2c<\/h3>\n
\u4eca\u3001\u79c1\u305f\u3061\u306f\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u3093\u3060\u306e\u3067\u3001\u305d\u308c\u3092\u5b66\u7fd2\u3057\u3001\u65b0\u3057\u3044\u30c7\u30fc\u30bf\u306b\u4e88\u6e2c\u3092\u8a66\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u305d\u306e\u305f\u3081\u306b\u306f\u3001\u307e\u305a\u63a8\u5b9a\u5668\u3092\u4f5c\u6210\u3057\u3001\u305d\u306efit\u30e1\u30bd\u30c3\u30c9\u3092\u547c\u3073\u51fa\u3059\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
from sklearn import svm\r\nfrom sklearn import datasets\r\n# Load dataset\r\niris = datasets.load_iris()\r\nclf = svm.LinearSVC()\r\n# learn from the data\r\nclf.fit(iris.data, iris.target)\r\n# predict for unseen data\r\nclf.predict([[ 5.0,  3.6,  1.3,  0.25]])\r\n# Parameters of model can be changed by using the attributes ending with an underscore\r\nprint(clf.coef_ )\r\n<\/code><\/pre>\n
\"Scikit<\/div>\n
Scikit Learn\u306e\u7dda\u5f62\u56de\u5e30<\/h3>\n
scikit-learn\u3092\u4f7f\u7528\u3057\u3066\u3001\u3055\u307e\u3056\u307e\u306a\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u306f\u6bd4\u8f03\u7684\u7c21\u5358\u3067\u3059\u3002\u307e\u305a\u3001\u56de\u5e30\u306e\u30b7\u30f3\u30d7\u30eb\u306a\u4f8b\u3067\u59cb\u3081\u307e\u3057\u3087\u3046\u3002<\/p>\n
#import the model\r\nfrom sklearn import linear_model\r\nreg = linear_model.LinearRegression()\r\n# use it to fit a data\r\nreg.fit ([[0, 0], [1, 1], [2, 2]], [0, 1, 2])\r\n# Let's look into the fitted data\r\nprint(reg.coef_)\r\n<\/code><\/pre>\n
\"python<\/div>\n
k-\u6700\u8fd1\u508d\u6cd5\u5206\u985e\u5668<\/h3>\n
\u7c21\u5358\u306a\u5206\u985e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u8a66\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u3053\u306e\u5206\u985e\u5668\u306f\u3001\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30b5\u30f3\u30d7\u30eb\u3092\u8868\u73fe\u3059\u308b\u305f\u3081\u306b\u30dc\u30fc\u30eb\u30c4\u30ea\u30fc\u306b\u57fa\u3065\u3044\u305f\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
from sklearn import datasets\r\n# Load dataset\r\niris = datasets.load_iris()\r\n# Create and fit a nearest-neighbor classifier\r\nfrom sklearn import neighbors\r\nknn = neighbors.KNeighborsClassifier()\r\nknn.fit(iris.data, iris.target)\r\n# Predict and print the result\r\nresult=knn.predict([[0.1, 0.2, 0.3, 0.4]])\r\nprint(result)\r\n<\/code><\/pre>\n
\"python<\/div>\n
K-\u5e73\u5747\u6cd5\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0<\/h3>\n
\u3053\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3001\u6700\u3082\u30b7\u30f3\u30d7\u30eb\u306a\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3067\u3059\u3002\u30bb\u30c3\u30c8\u306f\u300ck\u300d\u500b\u306e\u30af\u30e9\u30b9\u30bf\u306b\u5206\u5272\u3055\u308c\u3001\u5404\u89b3\u6e2c\u5024\u306f\u30af\u30e9\u30b9\u30bf\u306b\u5272\u308a\u5f53\u3066\u3089\u308c\u307e\u3059\u3002\u30af\u30e9\u30b9\u30bf\u304c\u53ce\u675f\u3059\u308b\u307e\u3067\u53cd\u5fa9\u7684\u306b\u3053\u308c\u304c\u884c\u308f\u308c\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u3067\u3001\u3053\u306e\u3088\u3046\u306a\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
from sklearn import cluster, datasets\r\n# load data\r\niris = datasets.load_iris()\r\n# create clusters for k=3\r\nk=3\r\nk_means = cluster.KMeans(k)\r\n# fit data\r\nk_means.fit(iris.data)\r\n# print results\r\nprint( k_means.labels_[::10])\r\nprint( iris.target[::10])\r\n<\/code><\/pre>\n
\"python<\/div>\n
\u7d50\u8ad6<\/h2>\n
\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Scikit-Learn\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u8907\u6570\u306e\u6a5f\u68b0\u5b66\u7fd2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3068\u306e\u4f5c\u696d\u304c\u7c21\u5358\u306b\u306a\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3057\u305f\u3002\u56de\u5e30\u3001\u5206\u985e\u3001\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u306e\u4f8b\u3082\u898b\u3066\u304d\u307e\u3057\u305f\u3002Scikit-Learn\u306f\u307e\u3060\u958b\u767a\u4e2d\u3067\u3001\u30dc\u30e9\u30f3\u30c6\u30a3\u30a2\u306b\u3088\u3063\u3066\u958b\u767a\u30fb\u7dad\u6301\u3055\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u3067\u975e\u5e38\u306b\u4eba\u6c17\u304c\u3042\u308a\u307e\u3059\u3002\u81ea\u5206\u81ea\u8eab\u306e\u4f8b\u3092\u8a66\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
Scikit Learn\u3092\u65e5\u672c\u8a9e\u3067\u8868\u73fe\u3059\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308a\u307e\u3059\uff1a \u30b5\u30a4\u30ad\u30c3\u30c8\u30fb\u30e9\u30fc\u30f3 Python\u306eScikit-learn Scikit\u306f\u3001\u307b\u3068\u3093\u3069\u304cPython\u3067\u66f8\u304b\u308c\u3066\u304a\u308a\u3001\u4e00\u90e8\u306e\u30b3\u30a2\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3055\u3089\u306a\u308b\u30d1\u30d5 […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[31,26],"class_list":["post-808","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-python","tag-26"],"yoast_head":"\nPython\u306eSciKit Learn\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb(Note: The given phrase is already in English, so it cannot be paraphrased into Japanese. However, if you are looking for a translation into Japanese, the provided phrase is already a suitable option.) - Blog - Silicon Cloud<\/title>\n<meta name=\"description\" content=\"Python\u306eSciKit Learn\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb(Note: The given phrase is already in English, so it cannot be paraphrased into Japanese. 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