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f1_score — scikit-learn 1.8.0 documentation
2 , 0 , 1 , 2 ] >>> y_pred = [ 0 , 2 , 1 , 0 , 0...is: \[\text{F1} = \frac{2 * \text{TP}}{2 * \text{TP} + \text{FP}...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html -
Curve Fitting with Bayesian Ridge Regression — ...
sin ( 2 * np . pi * x ) size = 25 rng..., axes = plt . subplots ( 1 , 2 , figsize = ( 8 , 4 )) for i ,...scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html -
test.mpp
ipsum dolor sit amet - 開始タスク 2. Task 2: consectetur adipiscing elit...Test User - テストユーザー - Resource 2: Fess Team - Fessチーム Notes: This...raw.githubusercontent.com/codelibs/fess-testdata/master/files/msoffice/test.mpp -
CountVectorizer — scikit-learn 1.8.0 documentation
2) means unigrams and bigrams, and (2, 2) means only...= 'word' , ngram_range = ( 2 , 2 )) >>> X2 = vectorizer2 . fit_transform...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
NotFittedError — scikit-learn 1.8.0 documentation
2 ], [ 2 , 3 ], [ 3 , 4 ]]) ... except...scikit-learn.org/stable/modules/generated/sklearn.exceptions.NotFittedError.html -
safe_mask — scikit-learn 1.8.0 documentation
[ 2 ], [ 3 ], [ 4 ], [ 5 ]]) >>> condition...[ mask ] . toarray () array([[2], [3], [5]]) On this page This...scikit-learn.org/stable/modules/generated/sklearn.utils.safe_mask.html -
Elastic BBQ: Better Binary Quantization in Luce...
( 1 < < 0 ) + ( 2 < < 1 ) + ( 1 < < 2 ) + ( 2 < < 3 ) = 25 = ...= ( 1 << 0 ) + ( 2 << 1 ) + ( 1 << 2 ) + ( 2 << 3 ) = 25 Same...www.elastic.co/search-labs/blog/better-binary-quantization-lucene-elasticsearch -
murmurhash3_32 — scikit-learn 1.8.0 documentation
to a signed int from -(2 ** 31) to 2 ** 31 - 1 Examples >>> from...to an unsigned int from 0 to 2 ** 32 - 1 False: the results is...scikit-learn.org/stable/modules/generated/sklearn.utils.murmurhash3_32.html -
MultiOutputRegressor — scikit-learn 1.8.0 docum...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...coefficient of determination, \(R^2\) , is defined as \((1 - \frac{u}{v})\)...scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html -
oas — scikit-learn 1.8.0 documentation
formula (23) states that 2/p (p being the number of features)...because for a large p, the value of 2/p is so small that it doesn’t...scikit-learn.org/stable/modules/generated/oas-function.html