Data analysis using fuzzy expressions: creating comprehensible computional models from data
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Linz
Trauner
2005
|
| Schriftenreihe: | Schriften der Johannes-Kepler-Universität Linz
Reihe C, Technik und Naturwissenschaften ; 48 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XVI, 208 S. graph. Darst. |
| ISBN: | 3854879326 |
Internformat
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| 245 | 1 | 0 | |a Data analysis using fuzzy expressions |b creating comprehensible computional models from data |c Mario Drobics |
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Datensatz im Suchindex
| _version_ | 1804135350172385280 |
|---|---|
| adam_text | Contents
1
1.1
1.1.1
1.1.2
1.1.3
1.2
1.2.1
1.2.2
1.2.3
1.3
2
2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.2
2.3
2.3.1
2.3.2
2.3.3
2.3.4
2.4
2.4.1
2.4.2
2.4.3
2.4.4
2.4.5
2.5
2.6
2.6.1
2.6.2
2.7
2.8
2.8.1
2.8.2
3
3.1
3.1.1
3.1.2
3.2
3.2.1
3.2.2
3.2.3
3.3 Data Interpretation..................... 81
3.3.1
3.3.2
3.3.3
3.4
3.4.1
3.4.2
3.4.3
4
4.1
4.1.1
4.1.2
4.1.3
4.2
4.2.1
4.2.2
4.2.3
4.3
4.3.1
4.3.2
4.3.3
(FS-ID3)
4.3.4
Trees (FS-LiRT)
4.4
4.4.1
4.4.2
4.4.3
5
5.1
5.1.1
5.1.2
5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.3
5.3.1
5.4
5.4.1
5.4.2
5.4.3
6
6.1
6.2
A machine learning framework for
Technical
plex. Analytical models are often insufficient to describe and handle
this complexity. Data accumulations, on the other hand, are growing
at ever increasing speeds, providing a potential source of knowledge
and experience to understand and manage these processes.
This work is therefore concerned with the general problem of creating
comprehensible computational models from data. To derive such
models from data, various different methods like statistical regres¬
sion, artificial neural nets, and other data-mining based approaches
exist. Typically, however, the resulting models are either compre¬
hensible (e.g. rule based approaches) or accurate (e.g. neural nets),
referring a tough decision to the user. As in real world applications
often both aspects are of high importance, the need for methods
providing comprehensible and accurate models arises.
In this work a novel approach which uses fuzzy predicates to create
close-to natural language expressions describing the relations in the
data under investigation is presented. These expressions are not only
easily comprehensible, but can be used for classification and nume¬
rical prediction tasks as well. A further application of the proposed
methods is the characterization of general patterns in the data (e.g.
clusters) using linguistic expressions.
The concepts and methods described in this work have been suc¬
cessfully applied in a number of real world projects and are available
within the machine learning framework for
been mainly developed by the author.
|
| adam_txt |
Contents
1
1.1
1.1.1
1.1.2
1.1.3
1.2
1.2.1
1.2.2
1.2.3
1.3
2
2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.2
2.3
2.3.1
2.3.2
2.3.3
2.3.4
2.4
2.4.1
2.4.2
2.4.3
2.4.4
2.4.5
2.5
2.6
2.6.1
2.6.2
2.7
2.8
2.8.1
2.8.2
3
3.1
3.1.1
3.1.2
3.2
3.2.1
3.2.2
3.2.3
3.3 Data Interpretation. 81
3.3.1
3.3.2
3.3.3
3.4
3.4.1
3.4.2
3.4.3
4
4.1
4.1.1
4.1.2
4.1.3
4.2
4.2.1
4.2.2
4.2.3
4.3
4.3.1
4.3.2
4.3.3
(FS-ID3)
4.3.4
Trees (FS-LiRT)
4.4
4.4.1
4.4.2
4.4.3
5
5.1
5.1.1
5.1.2
5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.3
5.3.1
5.4
5.4.1
5.4.2
5.4.3
6
6.1
6.2
A machine learning framework for
Technical
plex. Analytical models are often insufficient to describe and handle
this complexity. Data accumulations, on the other hand, are growing
at ever increasing speeds, providing a potential source of knowledge
and experience to understand and manage these processes.
This work is therefore concerned with the general problem of creating
comprehensible computational models from data. To derive such
models from data, various different methods like statistical regres¬
sion, artificial neural nets, and other data-mining based approaches
exist. Typically, however, the resulting models are either compre¬
hensible (e.g. rule based approaches) or accurate (e.g. neural nets),
referring a tough decision to the user. As in real world applications
often both aspects are of high importance, the need for methods
providing comprehensible and accurate models arises.
In this work a novel approach which uses fuzzy predicates to create
close-to natural language expressions describing the relations in the
data under investigation is presented. These expressions are not only
easily comprehensible, but can be used for classification and nume¬
rical prediction tasks as well. A further application of the proposed
methods is the characterization of general patterns in the data (e.g.
clusters) using linguistic expressions.
The concepts and methods described in this work have been suc¬
cessfully applied in a number of real world projects and are available
within the machine learning framework for
been mainly developed by the author. |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Drobics, Mario |
| author_facet | Drobics, Mario |
| author_role | aut |
| author_sort | Drobics, Mario |
| author_variant | m d md |
| building | Verbundindex |
| bvnumber | BV021579351 |
| classification_rvk | ST 301 ST 530 |
| ctrlnum | (OCoLC)314793580 (DE-599)BVBBV021579351 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Thesis Book |
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| genre_facet | Hochschulschrift |
| id | DE-604.BV021579351 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:41:10Z |
| indexdate | 2024-07-09T20:39:06Z |
| institution | BVB |
| isbn | 3854879326 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014795044 |
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| physical | XVI, 208 S. graph. Darst. |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | Trauner |
| record_format | marc |
| series | Schriften der Johannes-Kepler-Universität Linz |
| series2 | Schriften der Johannes-Kepler-Universität Linz : Reihe C, Technik und Naturwissenschaften |
| spelling | Drobics, Mario Verfasser aut Data analysis using fuzzy expressions creating comprehensible computional models from data Mario Drobics Linz Trauner 2005 XVI, 208 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Schriften der Johannes-Kepler-Universität Linz : Reihe C, Technik und Naturwissenschaften 48 Zugl.: Linz, Univ., Diss., 2005 Prognose (DE-588)4047390-9 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Fuzzy-Logik (DE-588)4341284-1 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Prognose (DE-588)4047390-9 s Datenanalyse (DE-588)4123037-1 s Fuzzy-Logik (DE-588)4341284-1 s DE-188 Schriften der Johannes-Kepler-Universität Linz Reihe C, Technik und Naturwissenschaften ; 48 (DE-604)BV009806089 48 Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014795044&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014795044&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Drobics, Mario Data analysis using fuzzy expressions creating comprehensible computional models from data Schriften der Johannes-Kepler-Universität Linz Prognose (DE-588)4047390-9 gnd Datenanalyse (DE-588)4123037-1 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
| subject_GND | (DE-588)4047390-9 (DE-588)4123037-1 (DE-588)4341284-1 (DE-588)4113937-9 |
| title | Data analysis using fuzzy expressions creating comprehensible computional models from data |
| title_auth | Data analysis using fuzzy expressions creating comprehensible computional models from data |
| title_exact_search | Data analysis using fuzzy expressions creating comprehensible computional models from data |
| title_exact_search_txtP | Data analysis using fuzzy expressions creating comprehensible computional models from data |
| title_full | Data analysis using fuzzy expressions creating comprehensible computional models from data Mario Drobics |
| title_fullStr | Data analysis using fuzzy expressions creating comprehensible computional models from data Mario Drobics |
| title_full_unstemmed | Data analysis using fuzzy expressions creating comprehensible computional models from data Mario Drobics |
| title_short | Data analysis using fuzzy expressions |
| title_sort | data analysis using fuzzy expressions creating comprehensible computional models from data |
| title_sub | creating comprehensible computional models from data |
| topic | Prognose (DE-588)4047390-9 gnd Datenanalyse (DE-588)4123037-1 gnd Fuzzy-Logik (DE-588)4341284-1 gnd |
| topic_facet | Prognose Datenanalyse Fuzzy-Logik Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014795044&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014795044&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV009806089 |
| work_keys_str_mv | AT drobicsmario dataanalysisusingfuzzyexpressionscreatingcomprehensiblecomputionalmodelsfromdata |