On the public citation graph

Knowledge discovery in data streams with regression tree methods

https://doi.org/10.1002/widm.51
0 signed · 89 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/for.3980140503openalex-snapshot
Highest‐density forecast regions for nonlinear and non‐normal time series models
inferredcites →https://doi.org/10.1002/widm.8openalex-snapshot
Classification and regression trees
inferredcites →https://doi.org/10.1007/3-540-70659-3_2openalex-snapshot
Machine Learning for Sequential Data: A Review
inferredcites →https://doi.org/10.1007/978-0-306-47630-3_21openalex-snapshot
Prediction Intervals for Time-Series Forecasting
inferredcites →https://doi.org/10.1007/978-1-4419-0320-4openalex-snapshot
Time Series: Theory and Methods
inferredcites →https://doi.org/10.1007/978-3-540-39592-8_8openalex-snapshot
Comparing Simplification Methods for Model Trees with Regression and Splitting Nodes
inferredcites →https://doi.org/10.1007/978-3-642-21551-3openalex-snapshot
Handbook of computational statistics : concepts and methods
inferredcites →https://doi.org/10.1007/978-3-662-04323-3openalex-snapshot
Nonlinear System Identification
inferredcites →https://doi.org/10.1007/bf00116895openalex-snapshot
Incremental Learning from Noisy Data
inferredcites →https://doi.org/10.1007/bfb0017010openalex-snapshot
On estimating probabilities in tree pruning
inferredcites →https://doi.org/10.1007/s10618-010-0198-2openalex-snapshot
Mixed-membership naive Bayes models
inferredcites →https://doi.org/10.1007/s10618-010-0201-yopenalex-snapshot
Learning model trees from evolving data streams
inferredcites →https://doi.org/10.1007/s10994-005-1121-8openalex-snapshot
Incremental Learning of Linear Model Trees
inferredcites →https://doi.org/10.1007/s11634-007-0015-yopenalex-snapshot
A recursive partitioning tool for interval prediction
inferredcites →https://doi.org/10.1016/0031-3203(80)90029-1openalex-snapshot
A combined nonparametric approach to feature selection and binary decision tree design
inferredcites →https://doi.org/10.1016/b978-1-55860-307-3.50037-xopenalex-snapshot
Combining Instance-Based and Model-Based Learning
inferredcites →https://doi.org/10.1016/b978-155860869-6/50036-6openalex-snapshot
Multi-Dimensional Regression Analysis of Time-Series Data Streams
inferredcites →https://doi.org/10.1016/c2009-0-19715-5openalex-snapshot
Data Mining: Practical Machine Learning Tools and Techniques
inferredcites →https://doi.org/10.1016/j.asoc.2007.11.003openalex-snapshot
Info-fuzzy algorithms for mining dynamic data streams
inferredcites →https://doi.org/10.1016/j.csda.2006.02.006openalex-snapshot
Prediction intervals for regression models
inferredcites →https://doi.org/10.1016/j.inffus.2005.05.005openalex-snapshot
Real-time data mining of non-stationary data streams from sensor networks
inferredcites →https://doi.org/10.1016/s0167-9473(99)00056-0openalex-snapshot
Nonparametric conditional predictive regions for time series
inferredcites →https://doi.org/10.1017/cbo9781107049994openalex-snapshot
Forecasting, Structural Time Series Models and the Kalman Filter
inferredcites →https://doi.org/10.1023/a:1007421302149openalex-snapshot
Using Model Trees for Classification
inferredcites →https://doi.org/10.1023/a:1007604202679openalex-snapshot
Learning Changing Concepts by Exploiting the Structure of Change
inferredcites →https://doi.org/10.1080/01621459.1963.10500855openalex-snapshot
Problems in the Analysis of Survey Data, and a Proposal
inferredcites →https://doi.org/10.1080/01621459.1988.10478652openalex-snapshot
Tree-Structured Classification Via Generalized Discriminant Analysis
inferredcites →https://doi.org/10.1109/icdmw.2009.30openalex-snapshot
Induction of Mean Output Prediction Trees from Continuous Temporal Meteorological Data
inferredcites →https://doi.org/10.1109/tpami.2004.1273937openalex-snapshot
Top-down induction of model trees with regression and splitting nodes
inferredcites →https://doi.org/10.1142/5210openalex-snapshot
Data Mining in Time Series Databases
inferredcites →https://doi.org/10.1142/9789812565402_0001openalex-snapshot
SEGMENTING TIME SERIES: A SURVEY AND NOVEL APPROACH
inferredcites →https://doi.org/10.1142/s0129065797000380openalex-snapshot
Understanding Time-Series Networks: A Case Study in Rule Extraction
inferredcites →https://doi.org/10.1145/1150402.1150531openalex-snapshot
YALE
inferredcites →https://doi.org/10.1145/1281192.1281273openalex-snapshot
Scalable look-ahead linear regression trees
inferredcites →https://doi.org/10.1145/1557019.1557041openalex-snapshot
New ensemble methods for evolving data streams
inferredcites →https://doi.org/10.1145/1557019.1557060openalex-snapshot
Issues in evaluation of stream learning algorithms
inferredcites →https://doi.org/10.1162/089976698300016963openalex-snapshot
Constructive Incremental Learning from Only Local Information
inferredcites →https://doi.org/10.1198/004017004000000590openalex-snapshot
Variable Selection for 1D Regression Models
inferredcites →https://doi.org/10.1198/1061860032544openalex-snapshot
A General Framework for Mining Massive Data Streams
inferredcites →https://doi.org/10.1214/aos/1176347963openalex-snapshot
Multivariate Adaptive Regression Splines
inferredcites →https://doi.org/10.2307/1910133openalex-snapshot
Tests of Equality Between Sets of Coefficients in Two Linear Regressions
inferredcites →https://doi.org/10.2307/2287869openalex-snapshot
Forecasting in Business and Economics.
inferredcites →https://doi.org/10.2307/2289508openalex-snapshot
An Introduction to Statistical Quality Control.
inferredcites →https://doi.org/10.2307/2289741openalex-snapshot
Time Series Analysis: Univariate and Multivariate Methods.
inferredcites →https://doi.org/10.2307/2530946openalex-snapshot
Classification and Regression Trees.
inferredcites →https://doi.org/10.2307/2986296openalex-snapshot
An Exploratory Technique for Investigating Large Quantities of Categorical Data
inferredcites →https://doi.org/10.3233/ida-2002-6203openalex-snapshot
Online classification of nonstationary data streams
inferredcites →https://doi.org/10.3233/ida-2009-0377openalex-snapshot
A system for analysis and prediction of electricity-load streams
inferredcites →https://doi.org/10.48550/arxiv.1010.4784openalex-snapshot
Learning under Concept Drift: an Overview

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.5055592openalex-extracted
Hybrid Machine Learning for Crop Yield Prediction Using Modified Three Way Decision and Knn Algorithms in Abrupt Concept Drift Environment
inferred← citeshttps://doi.org/10.1007/978-3-319-34099-9_56openalex-snapshot
A Meta-Learning Approach to Methane Concentration Value Prediction
inferred← citeshttps://doi.org/10.1007/978-3-319-63962-8_327-1openalex-snapshot
Reinforcement Learning, Unsupervised Methods, and Concept Drift in Stream Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-63962-8_329-1openalex-snapshot
Online Machine Learning Algorithms over Data Streams
inferred← citeshttps://doi.org/10.1007/978-3-319-77525-8_327openalex-snapshot
Reinforcement Learning, Unsupervised Methods, and Concept Drift in Stream Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-77525-8_329openalex-snapshot
Online Machine Learning Algorithms over Data Streams
inferred← citeshttps://doi.org/10.1007/978-3-319-91253-0_3openalex-snapshot
On the Global Convergence of the Parzen-Based Generalized Regression Neural Networks Applied to Streaming Data
inferred← citeshttps://doi.org/10.1007/s00477-024-02739-7openalex-snapshot
Discharge coefficient estimation of modified semi-cylindrical weirs using machine learning approaches
inferred← citeshttps://doi.org/10.1007/s10586-024-04465-9openalex-snapshot
An online ensemble method for auto-scaling NFV-based applications in the edge
inferred← citeshttps://doi.org/10.1007/s10973-019-08762-zopenalex-snapshot
Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid
inferred← citeshttps://doi.org/10.1007/s11269-019-02326-4openalex-snapshot
Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir
inferred← citeshttps://doi.org/10.1007/s13042-016-0513-3openalex-snapshot
Critical parameter analysis of Vertical Hoeffding Tree for optimized performance using SAMOA
inferred← citeshttps://doi.org/10.1016/j.asoc.2020.107008openalex-snapshot
Prediction of hydraulics performance in drain envelopes using Kmeans based multivariate adaptive regression spline
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2014.04.013openalex-snapshot
A GPU-based parallel method for evolutionary tree construction
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111465openalex-snapshot
Adaptive prediction of Rate of Penetration while oil-well drilling: A Hoeffding tree based approach
inferred← citeshttps://doi.org/10.1016/j.geoen.2025.213835openalex-snapshot
Advanced source rock characterization integrating pyrolysis, petrophysical logs, and machine learning in the unconventional Cane Creek reservoir, Utah
inferred← citeshttps://doi.org/10.1016/j.icheatmasstransfer.2020.104667openalex-snapshot
Application of M5 tree regression, MARS, and artificial neural network methods to predict the Nusselt number and output temperature of CuO based nanofluid flows in a car radiator
inferred← citeshttps://doi.org/10.1016/j.icheatmasstransfer.2021.105217openalex-snapshot
On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective – A comprehensive assessment of data analysis techniques
inferred← citeshttps://doi.org/10.1016/j.ins.2023.02.074openalex-snapshot
The L2 convergence of stream data mining algorithms based on probabilistic neural networks
inferred← citeshttps://doi.org/10.1016/j.neucom.2013.05.048openalex-snapshot
MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data
inferred← citeshttps://doi.org/10.1017/flo.2022.32openalex-snapshot
Real-time flow measurement system: physics-informed reconstruction and sampling strategy
inferred← citeshttps://doi.org/10.1021/acsengineeringau.2c00038openalex-snapshot
Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis
inferred← citeshttps://doi.org/10.1109/bigdata.2014.7004263openalex-snapshot
Regression trees for streaming data with local performance guarantees
inferred← citeshttps://doi.org/10.1109/icee.2018.8472481openalex-snapshot
Concept Drift Detection via Improved Deep Belief Network
inferred← citeshttps://doi.org/10.1109/ocit56763.2022.00055openalex-snapshot
Hybrid Regression Tree
inferred← citeshttps://doi.org/10.1109/sbrn.2012.50openalex-snapshot
Meta-Learning for Periodic Algorithm Selection in Time-Changing Data
inferred← citeshttps://doi.org/10.1109/tkde.2013.132openalex-snapshot
Pruning Incremental Linear Model Trees with Approximate Lookahead
inferred← citeshttps://doi.org/10.1111/coin.12071openalex-snapshot
Mining Evolving Data Streams with Particle Filters
inferred← citeshttps://doi.org/10.1111/insr.12016openalex-snapshot
Fifty Years of Classification and Regression Trees
inferred← citeshttps://doi.org/10.1145/2523813openalex-snapshot
A survey on concept drift adaptation
inferred← citeshttps://doi.org/10.21015/vtcs.v13i1.2093openalex-snapshot
Advancing NLP for Shahmukhi Punjabi: Word Embedding and Text Classification with a Novel Dataset
inferred← citeshttps://doi.org/10.29252/jwmr.9.18.157openalex-snapshot
Estimating Daily Reference Evapotranspiration using Data Mining Methods of Support Vector Regression and M5 Model Tree
inferred← citeshttps://doi.org/10.3233/idt-210236openalex-snapshot
Predicting aircraft maintenance timetofailure using the interval gradient regression tree algorithm
inferred← citeshttps://doi.org/10.3390/smartcities4010021openalex-snapshot
Concept Drift Adaptation Techniques in Distributed Environment for Real-World Data Streams
inferred← citeshttps://doi.org/10.3390/w16091246openalex-snapshot
Precipitation Modeling Based on Spatio-Temporal Variation in Lake Urmia Basin Using Machine Learning Methods
inferred← citeshttps://doi.org/10.4018/978-1-7998-9220-5.ch120openalex-snapshot
Aircraft Maintenance Prediction Tree Algorithms
inferred← citeshttps://doi.org/10.48550/arxiv.1802.05872openalex-snapshot
Online Machine Learning in Big Data Streams
inferred← citeshttps://doi.org/10.5120/ijca2015907398openalex-snapshot
An Interval Tree Approach to Predict Forest Fires using Meteorological Data
inferred← citeshttps://doi.org/10.5121/ijdms.2013.5304openalex-snapshot
A Survey on Educational Data Mining and Research Trends
inferred← citeshttps://doi.org/10.52547/jwmr.13.26.58openalex-snapshot
Temporal and Spatial Modeling of Groundwater Level in Bushehr Plain using Artificial Intelligence and Geostatistics
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.