svd_solver='randomized', random_state=random_state) X_embedded = pca.fit_transform(X).astype(np.float32, copy=False) elif self.init == 'random': # The embedding is initialized with iid samples from Gaussians with # standard deviation 1e-4. X_embedded = 1e-4 * random_state.randn(n...
105 106 107 108 109 110 111 112 113 114 importnumpy as np importsklearn fromsklearn.manifoldimportTSNE importcv2 # Random state. RS=20150101 importpandas as pd importmatplotlib.pyplot as plt importmatplotlib.patheffects as PathEffects importmatplotlib fromnumpyimport* # We import seaborn to make...
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X_train,X_test, y_train, y_test = cross_validation.train_test_split(train_data,train_target,test_size=0.4, random_state=0) 1. 2. 3. 参数解释 train_data:所要划分的样本特征集 train_target:所要划分的样本结果 test_size:样本占比,如果是整数的话就是样本的数量 random_state:是随机数的种子...
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Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML - trafilatura/tests/cache/en.wikipedia.org.tsne.html at 2639b2417c6db8e4df1d4f3b42f454076f7fa140 · purin-blog/traf
function. See :term: `Glossary <random_state>`. method : string (default: 'barnes_hut') By default the gradient calculation algorithm uses Barnes-Hut approximation running in O(NlogN) time. method='exact' will run on the slower, but exact, algorithm in O(N^2) time. The ...
int num_threads, int max_iter, int random_state, bool init_from_Y, int verbose, double early_exaggeration, double learning_rate);""") double early_exaggeration, double learning_rate, double *final_error);""") path = os.path.dirname(os.path.realpath(__file__)) try: @@ -105,12 +...
Issue Running pynndescent multiple times with the same random seed would return different results. Description of changes Fix. Cosmetic fixes. Includes Code changes Tests Documentation