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Nintendo Switch史上最高の名作だと思うゲームソフトランキング!3位「ゼルダの伝説...
抑えて1位に選ばれたのは… 駅弁が一番おいしい都道府県ランキング!3位 群馬、2位 宮城、気になる1位は… 第1話が衝撃...秋田、2位 東京、1位は… 10 方言がかわいい都道府県ランキング!3位 愛知県、2位 大分県、1位に選ばれたのは… 1 美人が多いと思う都道府県ランキング!3位...ranking.goo.ne.jp/column/10322/ -
Fess で作る Elasticsearch ベースの検索サーバー 〜 ロールベース検索編
fess.codelibs.org/ja/articles/article-2.html -
model_evaluation.rst.txt
1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...0, 0, 1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
plot_classifier_comparison.zip
C=1, random_state=42), GaussianProcessClass(1.0 * RBF(1.0),...max_features=1, random_state=42 ), MLPClassifier(alpha=1, max_iter=1000,...scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
cross_validation.rst.txt
[1., 1.], [-1., -1.], [2., 2.]]) >>> y = np.array([0, 1, 0,...3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3] [0 1]...scikit-learn.org/stable/_sources/modules/cross_validation.rst.txt -
plot_classifier_comparison.py
C=1, random_state=42), GaussianProcessClass(1.0 * RBF(1.0),...max_features=1, random_state=42 ), MLPClassifier(alpha=1, max_iter=1000,...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
auto_examples_python.zip
r"($\frac{1}{3}$, $\frac{1}{3}$, $\frac{1}{3}$)", xy=(1.0 / 3, 1.0 /...plt.annotate( r"($1$, $0$, $0$)", xy=(1, 0), xytext=(1, 0.1), xycoords="data",...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip -
plot_kmeans_digits.zip
1].min() - 1, reduced_data[:, 1].max() + 1 xx, yy =...reduced_data[:, 1].min() - 1, reduced_data[:, 1].max() + 1\nxx, yy =...scikit-learn.org/stable/_downloads/1393861b58df827d4c681b80a5be2472/plot_kmeans_digits.zip -
plot_discretization_strategies.rst.txt
8]]) centers_1 = np.array([[0, 0], [3, 1]]) # construct the...len(strategies) + 1, i) ax.scatter(X[:, 0], X[:, 1], edgecolors="k")...scikit-learn.org/stable/_sources/auto_examples/preprocessing/plot_discretization_strategies.rst.txt -
pydata-sphinx-theme.js
l={">":[1],">=":[0,1],"=":[0],"<=":[-1,0],"<":[-1]},d=Objec...("."),s.split(".")):a||s?a?-1:1:0})(e,t);return l[n].include...scikit-learn.org/stable/_static/scripts/pydata-sphinx-theme.js