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Variable size train sets, classification |
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Variable size train set, regression |
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SOAK algorithm: train/predict on subsets, classification |
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SOAK algorithm: train/predict on subsets, regression |
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Simple non-monotonic ROC curve |
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Generalized ROC curve metrics |
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Hidden Markov Model for 2d angular data |
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Accuracy of predicting qSIP data |
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BIC versus learned penalty in neuroblastoma data |
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Samples required to learn non-trivial regression model |
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Cross-validation for Breiman’s CART algorithm on SPAM data |
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Map and time series of Toby Hocking’s Bike Rides in 2009 |
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Greedy decision tree learning algorithm for binary classification (Breiman’s CART) |
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World Bank data (multiple selection, facets) |
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Gaussian Process models for sample selection |
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Classifying chest X-rays, plot confidence |
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Classifying Covid19 chest X-ray images |
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Overfitting using linear model polynomial degree and nearest neighbors |
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Overfitting using linear model polynomial degree |
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Initial/optimized AUM/AUC for change-point problems |
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Sugar Maple accuracy and variable selection |
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Table Mountain Pine accuracy and variable selection |
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Sugar Maple ROC curves and error/accuracy metrics |
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Table Mountain Pine ROC curves and error/accuracy metrics |
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L2-regularized (Ridge) least squares linear regression |
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Gradient descent with several step sizes for 1d linear regression in ozone data |
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Gradient descent for 1d linear regression in ozone data |
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Overfitting using linear model polynomial degree |
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Nearest neighbors algorithm for regression |
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Nearest neighbors for regression with 2D inputs |
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Nearest neighbors algorithm for classification |
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4 fold cross-validation |
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AIC/BIC change-point detection comparison using ROC curves |
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bacteria_fungi_conservative visualization |
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bacteria_fungi_conservative visualization |
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breakpoints select multiple segmentation models |
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