Category: Intellectual Data Analysis

Data Mining Research by Iryna Ivchenko

Data Mining Chapter 5: Supervised Learning Taxonomy — Classification and Regression

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Data Science
Data Science by Iryna Ivchenko & Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18626630  40stabilfr·wdophcgmx
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Score = Ref Trust (32 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

This chapter presents a hierarchical taxonomy of supervised l[REDACTED]g methods, organized along three primary dimensions: algorithmic architecture, l[REDACTED]g mechanism, and model interpretability. We trace the evolutionary development from early statistical classifiers through decision tree families, neural architectures, kernel methods, and ensemble strategies. Special attention is given ...

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Data Science by Iryna Ivchenko & Oleh Ivchenko DOI: 10.5281/zenodo.18626630 40stabilfr·wdophcgmx
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[g]Code—○Source code available on GitHub
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[x]Cited by0○Referenced by 0 other hub article(s)
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Data Mining Chapter 4: Taxonomic Framework Overview — Classifying the Field

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Data Science by Iryna Ivchenko & Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18665633  45stabilfr·wdophcgmx
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Score = Ref Trust (40 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The proliferation of data mining techniques over the past three decades has created an urgent need for systematic organization and classification of methodological approaches. This chapter establishes a comprehensive meta-taxonomic framework for understanding, categorizing, and relating the diverse landscape of data mining methods. We propose a three-dimensional classification scheme that organ...

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Data Science by Iryna Ivchenko & Oleh Ivchenko DOI: 10.5281/zenodo.18665633 45stabilfr·wdophcgmx
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[a]DOI0%○≥80% have a Digital Object Identifier
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[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (40 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Data Mining Chapter 2: Evolution of Data Mining Techniques (1960s-2000s)

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Data Science by Iryna Ivchenko & Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18749485  64stabilfr·wdophcgmx
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[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (72 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

This chapter chronicles the remarkable metamorphosis of data mining techniques across four transformative decades, from the pioneering expert systems of the 1960s to the sophisticated ensemble methods and standardized methodologies of the early 2000s. We trace the intellectual lineage from DENDRAL's rule-based reasoning through Quinlan's revolutionary decision tree algorithms, the renaissance o...

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Data Science by Iryna Ivchenko & Oleh Ivchenko DOI: 10.5281/zenodo.18749485 64stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources43%○≥80% from editorially reviewed sources
[t]Trusted86%✓≥80% from verified, high-quality sources
[a]DOI86%✓≥80% have a Digital Object Identifier
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[w]Words [REQ]5,837✓Minimum 2,000 words for a full research article. Current: 5,837
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18749485
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Score = Ref Trust (72 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Data Mining Chapter 3: The Modern Era — Big Data and Intelligent Mining

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Data Science by Iryna Ivchenko & Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18749487  65stabilfr·wdophcgmx
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[m]Diagrams6✓Mermaid architecture/flow diagrams. Current: 6
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (74 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

This chapter chronicles the revolutionary transformation of data mining during the big data era, spanning from Google's MapReduce paradigm in 2004 to the present age of intelligent, automated mining systems. We examine how the confluence of distributed computing, deep l[REDACTED]g, and cloud infrastructure fundamentally redefined both the scale and sophistication of knowledge discovery from dat...

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Data Science by Iryna Ivchenko & Oleh Ivchenko DOI: 10.5281/zenodo.18749487 65stabilfr·wdophcgmx
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (74 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Data Mining Chapter 1: The Genesis of Data Mining — From Statistics to Discovery

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Data Science by Iryna Ivchenko & Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18749494  63stabilfr·wdophcgmx
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (71 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

This chapter traces the fascinating journey of data mining from its embryonic roots in 19th-century statistics to its crystallization as a formal discipline in the 1990s. We explore how Francis Galton's pioneering work on regression analysis and Karl Pearson's correlation coefficients laid the mathematical groundwork for pattern discovery. The narrative advances through the computational revolu...

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Data Science by Iryna Ivchenko & Oleh Ivchenko DOI: 10.5281/zenodo.18749494 63stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources43%○≥80% from editorially reviewed sources
[t]Trusted86%✓≥80% from verified, high-quality sources
[a]DOI86%✓≥80% have a Digital Object Identifier
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[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18749494
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]7%✗≥60% of references from 2025–2026. Current: 7%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams6✓Mermaid architecture/flow diagrams. Current: 6
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (71 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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