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SGD: Maximum margin separating hyperplane — sci...
Y = make_blobs ( n_samples = 50 , centers = 2 , random_state...random_state = 0 , cluster_std = 0.60 ) # fit the model clf = SGDClassifier...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html -
7.2. Feature extraction — scikit-learn 1.7.2 do...
array(['pos+1=PP', 'pos-1=NN', 'pos-2=DT', 'word+1=on', 'word-1=cat',...TfidfTransformer(norm='l2', use_idf=True, smooth_idf=True, sublinear_tf=False)...scikit-learn.org/stable/modules/feature_extraction.html -
SAStruts での利用
-DgroupId=org.example -DartifactId=sample -Dversion=1.0.0-SNAPSHOT...-DarchetypeRepository=http://maven.seasar.org/maven2/ \ -DarchetypeGroupId=org.seasar.sastruts...dbflute.seasar.org/maven/plugin/ja/sastruts.html -
AdaBoostClassifier — scikit-learn 1.7.2 documen...
special cases with k == 1 , otherwise k==n_classes . For binary...special cases with k == 1 , otherwise k==n_classes . For binary...scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html -
LarsCV — scikit-learn 1.7.2 documentation
precompute = 'auto' , cv = None , max_n_alphas = 1000 , n_jobs = None...fit_intercept = True , verbose = False , max_iter = 500 , precompute...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LarsCV.html -
Illustration of Gaussian process classification...
s = 30 , c = Y , cmap = plt . cm . Paired , edgecolors = ( 0...figsize = ( 10 , 5 )) kernels = [ 1.0 * RBF ( length_scale = 1.15...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
「【コツコツ作業が得意な方】感情タグ付け作業」の仕事依頼【ジョブハブ】
＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝ 下記内容をご確認いただき、エントリー・提案をお願い致します。...jobhub.jp/jobs/34369 -
H2 Databaseの取扱い | DBFlute
; schema = [SCHEMA] ; user = [dbuser] ; password = [dbpassword]...edb ; schema = PUBLIC ; user = sa ; password = } databaseInfoMap.dfprop...dbflute.seasar.org/ja/manual/reference/dbway/h2/index.html -
f1_score — scikit-learn 1.7.2 documentation
labels = None , pos_label = 1 , average = 'binary' , sample_weight...sample_weight = None , zero_division = 'warn' ) [source] # Compute...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html -
KMeans — scikit-learn 1.7.2 documentation
max_iter = 300 , tol = 0.0001 , verbose = 0 , random_state = None...n_clusters = 8 , * , init = 'k-means++' , n_init = 'auto' , max_iter...scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html