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MNT Clean up examples
* chmod -x * remove Python shebang from examples: #!/usr/bin/python
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examples/classification/plot_classifier_comparison.py

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# -*- coding: utf-8 -*-
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Classifier comparison

examples/cluster/plot_cluster_iris.py

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K-means Clustering

examples/cluster/plot_digits_agglomeration.py

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Feature agglomeration

examples/cluster/plot_face_compress.py

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Vector Quantization Example

examples/compose/plot_compare_reduction.py

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"""
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=================================================================

examples/compose/plot_digits_pipe.py

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Pipelining: chaining a PCA and a logistic regression

examples/compose/plot_transformed_target.py

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Effect of transforming the targets in regression model

examples/datasets/plot_digits_last_image.py

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The Digit Dataset

examples/datasets/plot_iris_dataset.py

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The Iris Dataset

examples/decomposition/plot_pca_3d.py

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Principal components analysis (PCA)

examples/decomposition/plot_pca_iris.py

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PCA example with Iris Data-set

examples/gaussian_process/plot_gpc_isoprobability.py

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Iso-probability lines for Gaussian Processes classification (GPC)

examples/linear_model/plot_iris_logistic.py

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Logistic Regression 3-class Classifier

examples/linear_model/plot_lasso_lars.py

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Lasso path using LARS

examples/linear_model/plot_logistic.py

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Logistic function

examples/linear_model/plot_logistic_path.py

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Regularization path of L1- Logistic Regression

examples/linear_model/plot_multi_task_lasso_support.py

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Joint feature selection with multi-task Lasso

examples/linear_model/plot_ols.py

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Linear Regression Example

examples/linear_model/plot_ols_3d.py

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Sparsity Example: Fitting only features 1 and 2

examples/linear_model/plot_ols_ridge_variance.py

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Ordinary Least Squar F438 es and Ridge Regression Variance

examples/manifold/plot_manifold_sphere.py

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Manifold Learning methods on a severed sphere

examples/model_selection/grid_search_text_feature_extraction.py

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Sample pipeline for text feature extraction and evaluation

examples/preprocessing/plot_all_scaling.py

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Compare the effect of different scalers on data with outliers

examples/preprocessing/plot_discretization.py

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Using KBinsDiscretizer to discretize continuous features

examples/preprocessing/plot_discretization_classification.py

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======================

examples/preprocessing/plot_scaling_importance.py

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examples/svm/plot_rbf_parameters.py

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RBF SVM parameters
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``gamma_range`` steps will increase the resolution of the hyper-parameter heat
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import numpy as np

examples/svm/plot_svm_kernels.py

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SVM-Kernels

examples/svm/plot_svm_margin.py

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SVM Margins Example

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