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Importance of Feature Scaling — scikit-learn 1....
Feature scaling through standardization, also called Z-score normalization, is an important preprocessing step for many machine learning algorithms. It involves rescaling each feature such that it ...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html -
SVM Margins Example — scikit-learn 1.8.0 docume...
The plots below illustrate the effect the parameter C has on the separation line. A large value of C basically tells our model that we do not have that much faith in our data’s distribution, and wi...scikit-learn.org/stable/auto_examples/svm/plot_svm_margin.html -
Nearest Centroid Classification — scikit-learn ...
Sample usage of Nearest Centroid classification. It will plot the decision boundaries for each class.,., Total running time of the script:(0 minutes 0.135 seconds) Launch binder Launch JupyterLite ...scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html -
2. Unsupervised learning — scikit-learn 1.8.0 d...
Gaussian mixture models- Gaussian Mixture, Variational Bayesian Gaussian Mixture., Manifold learning- Introduction, Isomap, Locally Linear Embedding, Modified Locally Linear Embedding, Hessian Eige...scikit-learn.org/stable/unsupervised_learning.html -
3.2. Tuning the hyper-parameters of an estimato...
coupling parameters from a text documents feature extractor (n-gram...scikit-learn.org/stable/modules/grid_search.html -
Compare BIRCH and MiniBatchKMeans — scikit-lear...
This example compares the timing of BIRCH (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 25,000 samples and 2 features generated using make_blobs. B...scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html -
Probability Calibration curves — scikit-learn 1...
When performing classification one often wants to predict not only the class label, but also the associated probability. This probability gives some kind of confidence on the prediction. This examp...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
Model Complexity Influence — scikit-learn 1.8.0...
Demonstrate how model complexity influences both prediction accuracy and computational performance. We will be using two datasets:,- Diabetes dataset for regression. This dataset consists of 10 mea...scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html -
Gradient Boosting regularization — scikit-learn...
Illustration of the effect of different regularization strategies for Gradient Boosting. The example is taken from Hastie et al 2009 1. The loss function used is binomial deviance. Regularization v...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regularization.html -
Wikipedia principal eigenvector — scikit-learn ...
A classical way to assert the relative importance of vertices in a graph is to compute the principal eigenvector of the adjacency matrix so as to assign to each vertex the values of the components ...scikit-learn.org/stable/auto_examples/applications/wikipedia_principal_eigenvector.html