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Release Highlights for scikit-learn 1.5 — sciki...
array([[-1.1, 1.1, 1.1], [ 3.9, -1.2, 1.1], [ 0.1, 1.3, 1.1], [-0.1,...[-0.1, -1.4, -1.4], [-4.9, 1.5, -1.5], [ 0.1, 1.6, 1.6]]) Pairwise...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html -
1.4. Support Vector Machines — scikit-learn 1.8...
“0 vs 1”, “0 vs 2” , … “0 vs n”, “1 vs 2”, “1 vs 3”, “1 vs n”,...X = [[ 0 , 0 ], [ 1 , 1 ]] >>> y = [ 0 , 1 ] >>> clf = svm ....scikit-learn.org/stable/modules/svm.html -
1.5. Stochastic Gradient Descent — scikit-learn...
[ 1. , 1. ]] >>> y = [ 0 , 1 ] >>> clf = SGDClassifier...\Vert^2 + b\nu + \frac{1}{n} \sum_{i=1}^n \max(0, 1 - (\langle w, x_i...scikit-learn.org/stable/modules/sgd.html -
1.9. Naive Bayes — scikit-learn 1.8.0 documenta...
= P(x_i = 1 \mid y) x_i + (1 - P(x_i = 1 \mid y)) (1 - x_i)\]...\[P(x_i | y, x_1, \dots, x_{i-1}, x_{i+1}, \dots, x_n) = P(x_i | y),\]...scikit-learn.org/stable/modules/naive_bayes.html -
1.10. Decision Trees — scikit-learn 1.8.0 docum...
1 , 2 , 3 ]) . reshape ( - 1 , 1 ) >>> y = [ 0 , 1 , 1 , 1.... nan , - 1 , np . nan , 1 ]) . reshape ( - 1 , 1 ) >>> y = [...scikit-learn.org/stable/modules/tree.html -
1.6. Nearest Neighbors — scikit-learn 1.8.0 doc...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...scikit-learn.org/stable/modules/neighbors.html -
1.13. Feature selection — scikit-learn 1.8.0 do...
[1, 0], [0, 0], [1, 1], [1, 0], [1, 1]]) As expected, VarianceThreshold...0 , 0 , 1 ], [ 0 , 1 , 0 ], [ 1 , 0 , 0 ], [ 0 , 1 , 1 ], [ 0...scikit-learn.org/stable/modules/feature_selection.html -
1.7. Gaussian Processes — scikit-learn 1.8.0 do...
1.7.3. GPC examples # 1.7.3.1. Probabilistic predictions...features exceeds a few dozens. 1.7.1. Gaussian Process Regression...scikit-learn.org/stable/modules/gaussian_process.html -
1.16. Probability calibration — scikit-learn 1....
model [ 4 ] : \[p(y_i = 1 | f_i) = \frac{1}{1 + \exp(A f_i + B)} \,,\]...e.g. using many more features. 1.16.1. Calibration curves # Calibration...scikit-learn.org/stable/modules/calibration.html -
8.1. Toy datasets — scikit-learn 1.8.0 document...
length: 1.0 6.9 3.76 1.76 0.9490 (high!) petal width: 0.1 2.5 1.20...0.41 3.58 1.59 0.57 Colour Intensity: 1.3 13.0 5.1 2.3 Hue: 0.48...scikit-learn.org/stable/datasets/toy_dataset.html