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learning_curve — scikit-learn 1.6.1 documentation
exploit_incremental_learning = False , n_jobs = None , pre_dispatch = 'all' , verbose...verbose = 0 , shuffle = False , random_state = None , error_score...scikit-learn.org/stable/modules/generated/sklearn.model_selection.learning_curve.html -
移行 _project.shのJAVA_HOME | DBFlute
export ANT_OPTS=-Xmx512m export DBFLUTE_HOME=../mydbflute/dbflute-1.2.6...MY_PROPERTIES_PATH=build.properties JAVA_VERSION= 1.8+ # auto-setting...dbflute.seasar.org/ja/environment/upgrade/migration/theme/migrateshelljava.html -
MiniBatchKMeans — scikit-learn 1.6.1 documentation
n_clusters = 8 , * , init = 'k-means++' , max_iter = 100 , batch_size...batch_size = 1024 , verbose = 0 , compute_labels = True , random_state...scikit-learn.org/stable/modules/generated/sklearn.cluster.MiniBatchKMeans.html -
PCA — scikit-learn 1.6.1 documentation
n_components == min ( n_samples , n_features ) If n_components == 'mle'...n_components == 'mle' will interpret svd_solver == 'auto' as svd_solver...scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html -
related_projects.rst.txt
_related_projects: ========== Related Projects ========== Projects implementing...scikit-learn.org/stable/_sources/related_projects.rst.txt -
make_regression — scikit-learn 1.6.1 documentation
tail_strength = 0.5 , noise = 0.0 , shuffle = True , coef = False , random_state...n_samples = 100 , n_features = 100 , * , n_informative = 10 , n_targets...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html -
fbeta_score — scikit-learn 1.6.1 documentation
labels = None , pos_label = 1 , average = 'binary' , sample_weight...average = "macro" , zero_division = np . nan , beta = 0.5 ) 0.12......scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html -
Sample pipeline for text feature extraction and...
data_train = fetch_20newsgroups ( subset = "train" , categories = categories...categories , shuffle = True , random_state = 42 , remove = ( "headers"...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_text_feature_extraction.html -
precision_recall_fscore_support — scikit-learn ...
beta = 1.0 , labels = None , pos_label = 1 , average = None ,...warn_for = ('precision', 'recall', 'f-score') , sample_weight = None...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_fscore_support.html -
MetaFilter Podcast
<div class="svg-sprite" id="svg-sprite-container" style="display:none"></div>...type="text/javascript"> !function() { var static_server = 'dh...podcast.metafilter.com