Expert deduction rules in data mining with association rules: a case study

Rauch, Jan

doi:10.1007/s10115-018-1206-x

Cited by 17 publications

(30 citation statements)

References 26 publications

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“…In streaming data, unlimited data appears continuously and at a high speed, which will increase the difficulty of mining. Based on this, related scholars have proposed a HUSP-UT algorithm, which is based on a data stream tree structure [ 22 , 23 ]. A large number of experiments on real data sets show that HUSP-UT can effectively identify high-efficiency sequences.…”

Section: Related Workmentioning

confidence: 99%

Data Mining and Meta-Analysis of Psoriasis Based on Association Rules

Zhang

2022

Journal of Healthcare Engineering

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Psoriasis is a common chronic and recurrent disease in dermatology, which has a great impact on the physical and mental health of patients. Meta-analysis can evaluate the effectiveness and safety of defubao in the treatment of psoriasis vulgaris. This article observes psoriasis skin lesions treated with topical defubao and the changes in blood vessels under dermoscopy. Considering that the Apriori algorithm and the existing improved algorithm have the problems of ignoring the weight and repeatedly scanning the database, this paper proposes a matrix association rule method based on random forest weighting. This method uses the random forest algorithm to assign weights to each item in the data set, and introduces matrix theory to convert the transaction data set into a matrix form and store it, thereby improving operating efficiency. This article included 11 studies, of which 7 studies used the indicator “Researcher’s Overall Assessment” (IGA) to evaluate the efficacy, 5 studies used the “Patient Overall Assessment” (PGA) as the efficacy evaluation index, and Loss Area and Severity Index (PASI) was used as an observation index to evaluate the efficacy. Seven studies conducted safety comparisons. In this paper, IGA and PGA were used as evaluation indicators. The treatment effect of the defubao group was better than the calcipotriol group and the betamethasone group. The differences were statistically significant. The effect of the Fubao treatment for 8 weeks is significantly better than that of 4 weeks and 2 weeks, and the differences are statistically different. Using PASI as the evaluation index, a descriptive study was carried out, and it was found that after 4 weeks of treatment for psoriasis vulgaris, the average PASI reduction rate of patients was higher than that of the calcipotriol group and the betamethasone group. The safety evaluation found that after 8 weeks of treatment, the incidence of adverse events in the defubao group was significantly lower than that in the calcipotriol group.

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Section: Related Workmentioning

confidence: 99%

Data Mining and Meta-Analysis of Psoriasis Based on Association Rules

Zhang

2022

Journal of Healthcare Engineering

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“…D supp represents the ratio of data containing both X and Y to the entire data set. [12]. D conf is the ratio of data containing both X and Y to data containing X [12].…”

Section: Fuzzy Association Rule Miningmentioning

confidence: 99%

Transformer failure diagnosis using fuzzy association rule mining combined with case‐based reasoning

Guo

Wang

et al. 2020

IET Generation, Transmission & Distribution

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In the field of transformer failure diagnosis, the potential correlation between different characteristic parameters and failures is difficult to detect using traditional methods. Further, the quantities of inspection data have not been fully utilized. To improve the accuracy of transformer diagnosis, this study establishes a diagnosis model based on fuzzy association rules combined with case-based reasoning (CBR) to evaluate the failure types, fault locations, and cause of breakdown in power transformers. First, the inspection data of transformers are collected from several substations over 10 years. Then, the preprocessed data are randomly separated into training and testing sets. For the training set, fuzzy association rules are built for multiple parameters to narrow the search scope of base case preliminarily. Next, CBR is applied to determine the most similar cases. The failure information of the target transformer can be obtained in detail along with the most similar base case. Finally, the accuracy of the model is validated shown in case studies using the testing data set. The result demonstrates that the diagnosis model provides a higher accuracy than the classic IEC 60599 three-ratio method used in the current industry, which means that this diagnosis model has better performance on diagnosis accuracy.

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“…what is the overlap in their coverage in terms of specific instances. Second, explanations can be improved by utilisation of recently proposed techniques that use domain knowledge to filter or explain rules, such as expert deduction rules proposed by Rauch [126].…”

Section: Reiteration Effect Effects Of Validity and Illusiory Truthmentioning

confidence: 99%

“…Such explanation can be textual, but also can have a structured form. To decrease demands on the analyst, the explanation may only be required only if a conflict with existing knowledge has been automatically detected, for example, using approach proposed by Rauch [126].…”

Section: Ambiguity Aversionmentioning

confidence: 99%

A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models

Kliegr,

Bahník,

Fürnkranz

2018

Preprint

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While the interpretability of machine learning models is often equated with their mere syntactic comprehensibility, we think that interpretability goes beyond that, and that human interpretability should also be investigated from the point of view of cognitive science. In particular, the goal of this paper is to discuss to what extent cognitive biases may affect human understanding of interpretable machine learning models, in particular of logical rules discovered from data. Twenty cognitive biases are covered, as are possible debiasing techniques that can be adopted by designers of machine learning algorithms and software. Our review transfers results obtained in cognitive psychology to the domain of machine learning, aiming to bridge the current gap between these two areas. It needs to be followed by empirical studies specifically focused on the machine learning domain.

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Expert deduction rules in data mining with association rules: a case study

Cited by 17 publications

References 26 publications

Data Mining and Meta-Analysis of Psoriasis Based on Association Rules

Data Mining and Meta-Analysis of Psoriasis Based on Association Rules

Transformer failure diagnosis using fuzzy association rule mining combined with case‐based reasoning

A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models

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