Cite this DOI

B.Siva, & Ruhi (2023). A Method for Vibration Testing Decision Tree-Based Classification Systems. *Journal of Science & Technology*, *08*(09), 01–08. https://doi.org/10.46243/jst.2024.v8.i9.pp1-8

@article{bsiva2023method,
  author    = {B.Siva and Ruhi},
  title     = {{A Method for Vibration Testing Decision Tree-Based Classification Systems}},
  journal   = {Journal of Science \& Technology},
  year      = {2023},
  month     = {sep},
  volume    = {08},
  number    = {09},
  pages     = {01--08},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2024.v8.i9.pp1-8},
  url       = {https://doi.org/10.46243/jst.2024.v8.i9.pp1-8},
  language  = {en},
  abstract  = {"Without any intervention from a person, computers are capable of "learning" new things by analyzing data in various ways (training and testing) and making conclusions. One application of ML is decision trees. Many diverse disciplines make use of decision tree techniques. These algorithms have a wide variety of potential applications, including search engines, text extraction, and companies that provide medical certifications. Decision tree algorithms that are both accurate and affordable are now at our fingertips. Whenever a choice is necessary, it is critical to know what the best choice is. We present three decision tree algorithms in this study: ID3, C4.5, and CART. We use tools like WEKA, ML, and DT.}
}

TY  - JOUR
TI  - A Method for Vibration Testing Decision Tree-Based Classification Systems
AU  - B.Siva
AU  - Ruhi
JO  - Journal of Science & Technology
PY  - 2023
DA  - 2023/09/07/
VL  - 08
IS  - 09
SP  - 01
EP  - 08
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - "Without any intervention from a person, computers are capable of "learning" new things by analyzing data in various ways (training and testing) and making conclusions. One application of ML is decision trees. Many diverse disciplines make use of decision tree techniques. These algorithms have a wide variety of potential applications, including search engines, text extraction, and companies that provide medical certifications. Decision tree algorithms that are both accurate and affordable are now at our fingertips. Whenever a choice is necessary, it is critical to know what the best choice is. We present three decision tree algorithms in this study: ID3, C4.5, and CART. We use tools like WEKA, ML, and DT.
DO  - 10.46243/jst.2024.v8.i9.pp1-8
UR  - https://doi.org/10.46243/jst.2024.v8.i9.pp1-8
ER  -

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    "URL": "https://doi.org/10.46243/jst.2024.v8.i9.pp1-8",
    "title": "A Method for Vibration Testing Decision Tree-Based Classification Systems",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
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    "volume": "08",
    "issue": "09",
    "page": "01-08",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "\"Without any intervention from a person, computers are capable of \"learning\" new things by analyzing data in various ways (training and testing) and making conclusions. One application of ML is decision trees. Many diverse disciplines make use of decision tree techniques. These algorithms have a wide variety of potential applications, including search engines, text extraction, and companies that provide medical certifications. Decision tree algorithms that are both accurate and affordable are now at our fingertips. Whenever a choice is necessary, it is critical to know what the best choice is. We present three decision tree algorithms in this study: ID3, C4.5, and CART. We use tools like WEKA, ML, and DT.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2024.v8.i9.pp1-8 gives all four in one JSON answer.