Cited by 1,400Statistical Methods and InferenceStatistical Methods and ApplicationsMachine Learning and Algorithms

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The elements of statistical learning: Data mining, inference, and prediction

Franklin, James·2005·The Mathematical Intelligencer

DOI 10.1007/bf02985802

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“We used the following ones: • K-Nearest Neighbors [38], • Support Vector Machine [39], • Multi-Layer Perceptron [40], • Extra Tree [41].”
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Empirical dynamic model deciphers more information on the nutrient (N)—phytoplankton (P)–zooplankton (Z) dynamics of Hooghly-Matla estuary, Sundarban, India
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“To avoid overfitting, [13,14], k-fold Cross Validation is used, [15].”
Method
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Hsieh, H.-P., Wu, D.-Y., Hung, K., Lim, S.-W., Chen, T.-Y., Fan-Chiang, Y., & Ko, C. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12040522 · Cited by 13
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Method
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“Single decision trees are prone to over-ﬁtting while random forest models use votes from several decision trees to reduce variance in predictions ( 36 ).”
Background
Theoretical Approaches of Machine Learning to Schizophrenia
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Supervised feature subset selection with ordinal optimization
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Speech-Based Automated Cognitive Impairment Detection From Remotely-Collected Cognitive Test Audio
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Deep NRSfM++: Towards Unsupervised 2D-3D Lifting in the Wild
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Ensemble feature selection using q-rung orthopair hesitant fuzzy multi criteria decision making extended to VIKOR
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Metric Learning-Guided Least Squares Classifier Learning
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“Due to the least squares loss between soft regression results and hard zero-one labels [14], LSR is not quite suitable for discretelabel classification task from a perspective of statistical learning theory [5], [6].”
Background
Molecular descriptor-enhanced graph neural network for energetic molecular property prediction
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Extended minimum-squared error algorithm for robust face recognition via auxiliary mirror samples
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“There are various boosting methods, including Gradient Boosting [3], AdaBoost [35], etc.”
Method
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“…consists of four steps: (1) calculate k nearest neighbors using kNN query, (2) map low-dimensional geometrical features to high-dimensional features using Multilayer Perceptron (MLP) [35], (3) channel weighting, and (4) aggregate features of nearest neighbor points into features of a single point.”
Method
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“, the three minute limit in Hastie et al. (2017)), using a simple training/test regime instead of v-fold cross-validation, and/or relying on validation results obtained in simplistic scenarios, where the optimal tuning parameter is easy to “spot”.”
BackgroundMethodResultInfluential
Increasing Trust in (Big) Data Analytics
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Two realizations of a general feature extraction framework
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“Both the Minimum Mean Squared Error (or Deviance) (MSE) and the “One-Standard-Error rule” (1SE) are available (Hastie et al., 2009).”
Background
Identification of geographical origin of beef by visible-near infrared hyperspectral recovery from color images
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“The pseudo-code of the method is given in Algorithm 1 (Hastie et al. 2005).”
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“Following [75], class probabilities can be computed using the logistic model that generalizes naturally to multiclass classification problem.”
Method
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“The value of K strongly depend on the overall quantity of the data and the suggested number of fold is between 5 to 10 fold [90,91].”
Background
A versatile robotic platform for the design of natural, three-dimensional reaching and grasping tasks in monkeys
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Authors: Franklin, J.
Affiliations: UNSW Sydney (AU)
Corresponding author: Franklin, James
ORCID: Franklin, James
Venue: The Mathematical Intelligencer
Publisher: Springer Science and Business Media LLC
Published: 2005-03
Volume: 27
Issue: 2
Pages: 83-85
ISSN: 0343-6993 (ISSN-L)
DOI: 10.1007/bf02985802
OpenAlex: W3215186461
Cited by: 1,400
References: 0
Citations by year: 2026: 104 · 2025: 126 · 2024: 58 · 2023: 74 · 2022: 100 · 2021: 101 · 2020: 194 · 2019: 92 · 2018: 60 · 2017: 79 · 2016: 137 · 2015: 72 · 2014: 54 · 2013: 42 · 2012: 21
Type: book review
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: The Mathematical Intelligencer (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
Keywords: statistical learning, data mining, statistical inference, prediction

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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