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PredictionErrorDisplay — scikit-learn 1.6.1 doc...
y_true == y_pred . Therefore, it is a diagonal line for kind="predictions"...X , y = load_diabetes ( return_X_y = True ) >>> ridge = Ridge...scikit-learn.org/stable/modules/generated/sklearn.metrics.PredictionErrorDisplay.html -
user_guide.rst.txt
_user_guide: ========== User Guide ========== .. toctree:: :numbered:...scikit-learn.org/stable/_sources/user_guide.rst.txt -
make_checkerboard — scikit-learn 1.6.1 document...
noise = 0.0 , minval = 10 , maxval = 100 , shuffle = True ,...rows , columns = make_checkerboard ( shape = ( 300 , 300 ), n_clusters...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_checkerboard.html -
Instrumenting your OpenAI-powered Python, Node....
r=snapshots&g=co.elastic.otel&a=elastic-otel-javaagent&v=LATEST'...OPENAI_API_KEY=sk-YOUR_API_KEY OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:8200...www.elastic.co/observability-labs/blog/elastic-opentelemetry-openai -
Confusion matrix — scikit-learn 1.6.1 documenta...
with iris = datasets . load_iris () X = iris . data y = iris . target...classifier = svm . SVC ( kernel = "linear" , C = 0.01 ) . fit...scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html -
scale — scikit-learn 1.6.1 documentation
axis = 0 , with_mean = True , with_std = True , copy = True )...and scale. axis {0, 1}, default=0 Axis used to compute the means...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html -
plot_pca_iris.zip
py """ ========== Principal Component Analysis...Analysis (PCA) on Iris Dataset ========== This example shows a well known...scikit-learn.org/stable/_downloads/99402c7ce7a6ab7fafcb48caa3c9447b/plot_pca_iris.zip -
grid_search_cross_validation.png
PixelInterleaved width=885, height=613, bitDepth=8, colorType=RGBAlpha, ...red=8, green=8, blue=8, alpha=8 RGB 8 8 8 8 613 1 1.0 1 8 8 8...scikit-learn.org/stable/_images/grid_search_cross_validation.png -
accuracy_score — scikit-learn 1.6.1 documentation
normalize == True and the number of samples with normalize == False...y_pred , * , normalize = True , sample_weight = None ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html -
normalize — scikit-learn 1.6.1 documentation
norm = 'l2' , * , axis = 1 , copy = True , return_norm = False...even with copy=False. return_norm bool, default=False Whether...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html
