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...m of decision making using the concept of piecewise-linear separability of datasets to categorize data. Two datasets are linearly separable if their [[convex hull]]s do not intersect. The meth ...

...ataset is imbalanced. It exploits the structures of conditional imbalanced datasets more efficiently than alternative methods, such as [[Logistic regression#Ca == Imbalanced datasets == ...

...nbsp;Hz. Figure 1. presents the graph for the Kolsky model (blue) with two datasets (left and right) and same data – attenuation with c_r=2000 m The SLS model (green) has two different datasets, ...

...lions of elements (when applied to the [[number-theoretic transform]], the datasets of the order of 10¹² elements were processed in mid-2000s{{sfn|A ...

...tzmaurice |first2=George |chapter=Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing [[File:EDA_example_-_Always_plot_your_data.jpg|alt=thirteen graphs of the datasets in the Datasaurus Dozen, visualized graphically and also summarized numeric ...

...013 |website=Virtual Library of Simulation Experiments: Test Functions and Datasets |publisher=Simon Fraser University |access-date=December 22, 2024}}</ref> ...

=== For datasets with a few variables – general log-linear models === === For datasets with hundreds of variables – decomposable models === ...

...the MSE with the signal power, enabling fair comparisons across different datasets and scales. An extension of RMSE, which allows for signal comparisons between different datasets and models with varying scales. ...

...icroarrays. Haplotype estimation methods are used in the analysis of these datasets and allow [[Imputation (genetics)|genotype imputation]]<ref>{{Cite journal ...HapMap Project]]. PHASE was limited by its speed and was not applicable to datasets from genome-wide association studies. ...

...MAFFT]], FSA is one of the few sequence alignment programs which can align datasets of hundreds or thousands of sequences. FSA uses a different optimization cr ...-Renyi theory of random graphs. This significantly reduces the runtimes of datasets and the computational cost of running the multiple alignments. ...

...erential privacy]] when releasing the results of computations on sensitive datasets. They work by adding carefully calibrated random noise, drawn from specific Let <math>\mathcal{D}</math> be a collection of all datasets and <math>f\colon \mathcal{D} \to \R</math> be a real-valued function. The ...

[[Head-related transfer function]]s (HRTF) datasets can be used to simplify the process insofar as a monaural IR can be measure ...

...ef>{{cite book |last1=Leskovec, Rajaraman, Ullman |title=Mining of Massive Datasets |date=2014 |publisher=Cambridge University Press |page=144 |edition=2nd |ur ...|first1=Anand |last2=Ullman |first2=Jeffrey David |title=Mining of Massive Datasets |url=https://books.google.com/books?id=OefRhZyYOb0C&pg=PA119 |accessdate=20 ...

...ndomly sampled [[Feature (machine learning)|feature maps]]. It is used for datasets that are too large for traditional kernel methods like [[support vector mac ...e with kernel SVMs. However, there was no way to train kernel SVM on large datasets. The two authors developed the random feature method to train those. ...

...ss to the dataset, but has access to public aggregate statistics about the datasets, which could be exact or distorted, for example by adding noise. If the pub ...

...etrieval]] systems when it is based not on Wikipedia, but on the [[List of datasets for machine-learning research#News articles|Reuters corpus of newswire arti ...easure of semantic relatedness (as opposed to [[semantic similarity]]). On datasets used to benchmark relatedness of words, ESA outperforms other algorithms, i ...

...ziz, D. M. (2023). Machine Learning for Imbalanced Data: Tackle Imbalanced Datasets Using Machine Learning and Deep Learning Techniques. (n.p.): Packt Publishi ...

==Datasets== ...ttps://saliency.tuebingen.ai/datasets.html MIT/Tübingen Saliency Benchmark datasets], for example. ...

| title = Assessment of global cloud datasets from satellites: Project and Database initiated by GEWEX Radiation Panel ...

...>Q\,\!</math> is its maximum difference when evaluated on two neighbouring datasets <math>D_1,D_2\in\mathcal{D}^n\,\!</math>: There are at most <math>2^{km}\,\!</math> output datasets and the probability that <math>q(D,\widehat{D})\leq -\alpha\,\!</math> is a ...