- Sort Score
- Num 10 results
- Language All
- Labels All
Results 1251 - 1260 of over 10,000 for 2 (0.21 seconds)
-
Artificial intelligence - Courses - IBM Developer
1–12 of 16 items Page of 2 pages 1 2 of 2 pages Previous page Next...developer.ibm.com/technologies/artificial-intelligence/courses/ -
Label Propagation digits: Demonstrating perform...
RandomState ( 2 ) indices = np . arange ( len...1.00 1.00 27 1 0.82 1.00 0.90 37 2 1.00 0.86 0.92 28 3 1.00 0.80...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html -
Reciprocal rank fusion | Reference
_id: 2 = 1.0/(1+3) + 1.0/(1+2) = 0.5833 _id: 3 = 1.0/(1+2) + 1.0/(1+1)...from=2, size=2 would return documents [ 2 , 3 ] with ranks [3, 4]...www.elastic.co/docs/reference/elasticsearch/rest-apis/reciprocal-rank-fusion -
AdaBoostRegressor — scikit-learn 1.8.0 do...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...algorithm known as AdaBoost.R2 [2]. Read more in the User Guide...scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostRegressor.html -
Working with Elastic Support: Best practices | ...
business day 2 business days - Development - - - 2 business days...Urgent (Level 1) High (Level 2) Normal (Level 3) Premium 30 minutes...www.elastic.co/support/welcome -
ClassicalMDS — scikit-learn 1.8.0 documen...
ClassicalMDS ( n_components = 2 , * , metric = 'euclidean' , metric_params...Parameters : n_components int, default=2 Number of embedding dimensions....scikit-learn.org/stable/modules/generated/sklearn.manifold.ClassicalMDS.html -
_safe_indexing — scikit-learn 1.8.0 docum...
2 ], [ 3 , 4 ], [ 5 , 6 ]]) >>>...select the first row array([1, 2]) >>> _safe_indexing...scikit-learn.org/stable/modules/generated/sklearn.utils._safe_indexing.html -
make_friedman1 — scikit-learn 1.8.0 docum...
2 ] - 0.5 ) ** 2 + 10 * X [:, 3 ] + 5 *...in Friedman [1] and Breiman [2]. Inputs X are independent features...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
neighbors.rst.txt
[-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]]) >>> nbrs...np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]]) >>> kdt...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
lasso_path — scikit-learn 1.8.0 documenta...
it is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...X = np . array ([[ 1 , 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]]) . T >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html