87 lines
2.9 KiB
BibTeX
87 lines
2.9 KiB
BibTeX
% @manual{scikit_classifier_comparison,
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% author = "scikit-learn",
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% title = "Classifier Comparison",
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% url = "https://scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html",
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% urldate = "2024-10-05"
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% }
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@manual{scikit_randomforestclassifier,
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author = "scikit-learn Documentation",
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title = "\texttt{RandomForestClassifier} API Reference",
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url = "https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html",
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urldate = "2024-10-06"
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}
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@manual{scikit_svc,
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author = "scikit-learn Documentation",
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title = "\texttt{SVC} API Reference",
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url = "https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html#sklearn.svm.SVC",
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urldate = "2024-10-06"
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}
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@manual{scikit_svm,
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author = "scikit-learn Documentation",
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title = "Support Vector Machines",
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url = "https://scikit-learn.org/stable/modules/svm.html",
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urldate = "2024-10-06"
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}
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@manual{scikit_kernel,
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author = "scikit-learn Documentation",
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title = "Plot classification boundaries with different SVM Kernels",
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url = "https://scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html#sphx-glr-auto-examples-svm-plot-svm-kernels-py",
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urldate = "2024-10-06"
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}
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@online{geekkernel,
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author = "GeeksforGeeks",
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title = "How to Choose the Best Kernel Function for SVMs",
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url = "https://www.geeksforgeeks.org/how-to-choose-the-best-kernel-function-for-svms/",
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urldate = "2024-10-06"
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}
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@online{ibm_randomforest,
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author = "IBM",
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title = "What is random forest?",
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url = "https://www.ibm.com/topics/random-forest",
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urldate = "2024-10-06"
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}
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@online{ibm_svm,
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author = "IBM",
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title = "What are support vector machines (SVMs)?",
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url = "https://www.ibm.com/topics/support-vector-machine",
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urldate = "2024-10-06"
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}
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@online{gandhiSVM,
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author = "Rohith Gandhi",
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title = "Support Vector Machine — Introduction to Machine Learning Algorithms",
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url = "https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47",
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urldate = "2024-10-06"
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}
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@book{understandingML,
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title = "Understanding Machine Learning: From Theory to Algorithms",
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author = "Shalev-Shwartz, Shai and Ben-David, Shai",
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year = "2014",
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publisher = "Cambridge University Press",
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% url = "https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/copy.html"
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}
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@online{scikit_ensembles,
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author = "scikit-learn Documentation",
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title = "Ensembles: Gradient boosting, random forests, bagging, voting, stacking",
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url = "https://scikit-learn.org/stable/modules/ensemble.html",
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urldate = "2024-10-06"
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}
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@article{breiman,
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author = "Breiman, Leo",
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title = "Random Forests",
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journal = "Machine Learning",
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year = "2001",
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volume = "45",
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page = "5-32",
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}
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