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  1. A demo of K-Means clustering on the handwritten...

    text documents using k-means Clustering text documents using...
    scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_digits.html
    Sat Apr 19 00:31:22 UTC 2025
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  2. Configurable chunking settings for inference AP...

    Ingest a document into the index Ingest the document into the...configurable chunking for document ingestion with semantic text...
    www.elastic.co/search-labs/blog/elasticsearch-chunking-inference-api-endpoints
    Wed Mar 26 00:35:39 UTC 2025
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  3. 6.3. Preprocessing data — scikit-learn 1.6.1 do...

    The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that is more suitable for the downstream esti...
    scikit-learn.org/stable/modules/preprocessing.html
    Sat Apr 19 00:31:21 UTC 2025
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  4. 1.13. Feature selection — scikit-learn 1.6.1 do...

    The classes in the sklearn.feature_selection module can be used for feature selection/dimensionality reduction on sample sets, either to improve estimators’ accuracy scores or to boost their perfor...
    scikit-learn.org/stable/modules/feature_selection.html
    Sat Apr 19 00:31:22 UTC 2025
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  5. Model-based and sequential feature selection — ...

    This example illustrates and compares two approaches for feature selection: SelectFromModel which is based on feature importance, and SequentialFeatureSelector which relies on a greedy approach. We...
    scikit-learn.org/stable/auto_examples/feature_selection/plot_select_from_model_diabetes.html
    Sat Apr 19 00:31:22 UTC 2025
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  6. Effect of varying threshold for self-training —...

    This example illustrates the effect of a varying threshold on self-training. The breast_cancer dataset is loaded, and labels are deleted such that only 50 out of 569 samples have labels. A SelfTrai...
    scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html
    Sat Apr 19 00:31:22 UTC 2025
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  7. A demo of the mean-shift clustering algorithm —...

    Reference: Dorin Comaniciu and Peter Meer, “Mean Shift: A robust approach toward feature space analysis”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2002. pp. 603-619. Generate...
    scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html
    Sat Apr 19 00:31:22 UTC 2025
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  8. Ordinary Least Squares and Ridge Regression Var...

    Due to the few points in each dimension and the straight line that linear regression uses to follow these points as well as it can, noise on the observations will cause great variance as shown in t...
    scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge_variance.html
    Sat Apr 19 00:31:22 UTC 2025
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  9. 1.10. Decision Trees — scikit-learn 1.6.1 docum...

    Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning s...
    scikit-learn.org/stable/modules/tree.html
    Sat Apr 19 00:31:21 UTC 2025
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  10. 7.1. Toy datasets — scikit-learn 1.6.1 document...

    scikit-learn comes with a few small standard datasets that do not require to download any file from some external website. They can be loaded using the following functions: These datasets are usefu...
    scikit-learn.org/stable/datasets/toy_dataset.html
    Sat Apr 19 00:31:22 UTC 2025
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