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SAFluteでビルドデプロイするやり方 | DBFlute
Sea_ConfigProperties = map:{ ... ; environmentMap = map:{ ; integration = $$b...production = $$baseDir$$/production/resources ; sea = $$baseDir$$/sea/resources...dbflute.seasar.org/ja/manual/function/helper/saflute/howto/builddeploy.html -
Target Encoder’s Internal Cross fitting — sciki...
transform_output = "pandas" ) ridge = Ridge ( alpha = 1e-6 , solver = "lsqr"...n_samples = 50_000 rng = np . random . RandomState ( 42 ) y = rng ....scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder_cross_val.html -
Scalable learning with polynomial kernel approx...
y = fetch_covtype ( return_X_y = True ) y [ y != 2 ] = 0 y...SVC ksvm = SVC ( C = 500.0 , kernel = "poly" , degree = 4 , coef0...scikit-learn.org/stable/auto_examples/kernel_approximation/plot_scalable_poly_kernels.html -
beta_divergence.png
encoding=ISO-8859-1, compression=none keyword=Software, value=Matplotlib...0.2540005 width=640, height=480, bitDepth=8, colorType=RGB, compr...scikit-learn.org/stable/_images/beta_divergence.png -
Decision Boundaries of Multinomial and One-vs-R...
n_samples = 1_000 , centers = centers , random_state = 40 ) transformation..., ax = plt . subplots ( figsize = ( 6 , 4 )) scatter = ax . scatter...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_multinomial.html -
Poisson regression and non-normal loss — scikit...
axes = plt . subplots ( nrows = 2 , ncols = 4 , figsize = ( 16..., ax = plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 12...scikit-learn.org/stable/auto_examples/linear_model/plot_poisson_regression_non_normal_loss.html -
L1 Penalty and Sparsity in Logistic Regression ...
clf_l1_LR = LogisticRegression ( C = C , penalty = "l1" , tol = 0.01...penalty = "l2" , tol = 0.01 , solver = "saga" ) clf_en_LR = LogisticRegression...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html -
Multilabel classification — scikit-learn 1.7.0 ...
if transform == "pca" : X = PCA ( n_components = 2 ) . fit_transform...elif transform == "cca" : X = CCA ( n_components = 2 ) . fit ( X...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multilabel.html -
Plot multi-class SGD on the iris dataset — scik...
mean ( axis = 0 ) std = X . std ( axis = 0 ) X = ( X - mean ) /...dataset X = iris . data [:, : 2 ] y = iris . target colors = "bry"...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html -
Single estimator versus bagging: bias-variance ...
* 10 - 5 X = np . sort ( X ) if n_repeat == 1 : y = f ( X ) +...X_train = [] y_train = [] for i in range ( n_repeat ): X , y = generate...scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html
