JP2018088087A5 - - Google Patents
Download PDFInfo
- Publication number
- JP2018088087A5 JP2018088087A5 JP2016230439A JP2016230439A JP2018088087A5 JP 2018088087 A5 JP2018088087 A5 JP 2018088087A5 JP 2016230439 A JP2016230439 A JP 2016230439A JP 2016230439 A JP2016230439 A JP 2016230439A JP 2018088087 A5 JP2018088087 A5 JP 2018088087A5
- Authority
- JP
- Japan
- Prior art keywords
- constraint
- data
- attribute
- attributes
- data analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000007405 data analysis Methods 0.000 claims 9
- 238000004458 analytical method Methods 0.000 claims 4
- 238000007619 statistical method Methods 0.000 claims 2
Claims (9)
前記説明変数から求められた前記制約を満たす1以上の属性の選択パターンに含まれる属性に対して、データ分析をする分析部と、
を備えるデータ分析装置。 From the data analyst explanatory variables, one or more of the constraints information used was formally described as decisions when selecting the attribute used to analyze, and one or more explanatory variables, one or more eyes variables And a reception unit for receiving
An analysis unit that analyzes data with respect to an attribute included in a selection pattern of one or more attributes satisfying the constraint determined from the explanatory variable;
Data analysis device comprising:
前記選択パターン生成用論理式を満たす前記選択パターンを取得する取得部、を備える請求項1に記載のデータ分析装置。 A generation unit configured to generate a logical expression for generating a selection pattern for generating the selection pattern from the constraint that is valid;
The data analysis device according to claim 1, further comprising: an acquisition unit that acquires the selection pattern that satisfies the selection pattern generation logical expression.
前記説明変数から求められた前記制約を満たす1以上の属性の選択パターンに含まれる属性に対して、データ分析をするデータ分析方法。 Accepting one or more constraints which formally describe information used as judgment material when the data analyst selects a target variable from a plurality of attributes, one or more explanatory variables, and one or more of the target variables;
A data analysis method in which data analysis is performed on an attribute included in a selection pattern of one or more attributes satisfying the constraint determined from the explanatory variable.
データ分析者が複数の属性から目的変数を選択する時に判断材料として使用する情報を形式的に記述した1以上の制約と、1以上の説明変数と、1以上の前記目的変数とを受け付ける受付ステップと、
前記説明変数から求められた前記制約を満たす1以上の属性の選択パターンに含まれる属性に対して、データ分析をする分析ステップと、
を備えるデータ分析プログラム。 A program for causing a computer to execute an apparatus for analyzing data,
Accepting step of accepting one or more constraints which formally describe information used as judgment material when data analyst selects an objective variable from a plurality of attributes, one or more explanatory variables, and one or more of the objective variables When,
Analyzing data with respect to an attribute included in a selection pattern of one or more attributes satisfying the constraint determined from the explanatory variable;
Data analysis program comprising:
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2016230439A JP6800716B2 (en) | 2016-11-28 | 2016-11-28 | Data analyzers, data analysis methods, and data analysis programs |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2016230439A JP6800716B2 (en) | 2016-11-28 | 2016-11-28 | Data analyzers, data analysis methods, and data analysis programs |
Publications (3)
Publication Number | Publication Date |
---|---|
JP2018088087A JP2018088087A (en) | 2018-06-07 |
JP2018088087A5 true JP2018088087A5 (en) | 2019-04-25 |
JP6800716B2 JP6800716B2 (en) | 2020-12-16 |
Family
ID=62494420
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP2016230439A Active JP6800716B2 (en) | 2016-11-28 | 2016-11-28 | Data analyzers, data analysis methods, and data analysis programs |
Country Status (1)
Country | Link |
---|---|
JP (1) | JP6800716B2 (en) |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP7246956B2 (en) * | 2019-02-13 | 2023-03-28 | 株式会社キーエンス | Data analysis device and data analysis method |
JP7246957B2 (en) * | 2019-02-13 | 2023-03-28 | 株式会社キーエンス | Data analysis device and data analysis method |
JP7189654B2 (en) * | 2020-01-06 | 2022-12-14 | Kddi株式会社 | Program, apparatus and method for estimating commercial value of real estate |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH1091612A (en) * | 1996-09-18 | 1998-04-10 | Nippon Telegr & Teleph Corp <Ntt> | Method and device for analyzing complacency decision program for sum product type logical expression |
JP2000020504A (en) * | 1998-06-30 | 2000-01-21 | Toshiba Corp | Method for explaining or predicting object variable and recording medium having recorded program for explaining or predicting object variable thereon |
JP5462750B2 (en) * | 2010-09-06 | 2014-04-02 | 新日鐵住金株式会社 | Molten steel temperature management method, apparatus and program |
-
2016
- 2016-11-28 JP JP2016230439A patent/JP6800716B2/en active Active
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11468664B2 (en) | Machine learning to predict cognitive image composition | |
TW202139004A (en) | Method and non-transitory computer-readable storage medium for time-series fault detection, fault classification, and transition analysis using a k-nearest-neighbor and logistic regression approach | |
SG10201807986SA (en) | Data records selection | |
JP2018088087A5 (en) | ||
JP2016024789A5 (en) | ||
JP2016512171A5 (en) | ||
JP2018536939A5 (en) | ||
JP2014229115A5 (en) | ||
MX2016017061A (en) | Weld sequencer part and statistical limits analyzer. | |
JP2013246681A5 (en) | ||
JP2015059965A5 (en) | ||
JP2017527013A5 (en) | ||
IN2013DE02920A (en) | ||
EP3376409A3 (en) | Method and apparatus for spatial data visualization | |
JP2013097467A5 (en) | ||
JP2018081350A5 (en) | ||
Conwell et al. | Large-scale benchmarking of diverse artificial vision models in prediction of 7T human neuroimaging data | |
JP2016200860A5 (en) | ||
Conwell et al. | What can 5.17 billion regression fits tell us about artificial models of the human visual system? | |
JP2022006189A (en) | Image processing method, pre-training model training method, equipment, and electronic device | |
CN111858927B (en) | Data testing method and device, electronic equipment and storage medium | |
JP2013246682A5 (en) | ||
Wang et al. | Defragging subgraph features for graph classification | |
US20200133819A1 (en) | Techniques for analyzing the proficiency of users of software applications | |
Sienou et al. | Risk driven process engineering in digital ecosystems: Modelling risk |