scholarly journals Tree species consistent co-occurrence in seasonal tropical forests: an approach through association rules analysis

2021 ◽  
Vol 30 (2) ◽  
pp. e006
Author(s):  
Cléber Rodrigo Souza ◽  
Vinícius Andrade Maia ◽  
Natália Aguiar-Campos ◽  
Camila Laís Farrapo ◽  
Rubens Manoel Santos
Keyword(s):  
Data Mining ◽  
Tropical Forests ◽  
Association Rules ◽  
Tree Species ◽  
Total Sample ◽  
Deciduous Forests ◽  
Permanent Plots ◽  
P Value ◽  
Semideciduous Forest ◽  
Association Rules Analysis

Aim of study: Aassessing the existence of consistent co-occurrence between tree species that characterize seasonal tropical forests, using the association rules analysis (ARA), that is a novel data mining methodology; and evaluate evaluating the taxonomic and functional similarities between associated species.Area of study: forty-four seasonal forest sites with permanent plots (40.2 ha of total sample) located in Southeast Brazil, from which we obtained species occurrences.Material and methods: we applied association rules analysis (ARA) to the dataset of species occurrence in sites considering the criteria of support equal to or greater than 0.63 and confidence equal to or greater than 0.8 to obtain the first set of associations rules between pairs of species. This set was then submitted to Fisher’s criteria exact p-value less than 0.05, lift equal to or greater than 1.1 and coverage equal to or greater than 0.63. We considered these criteria to be able to select non-random and consistent occurring associations.Main results: We obtained a final result of 238 rules for semideciduous forest and 11 rules for deciduous forests, composed of species characteristic of vegetation types. Co-occurrences are formed mainly by non-confamilial species, which have similar functional characteristics (potential size and wood density). There is a difference in the importance of co-occurrence between forest types, which tends to be less in deciduous forests.Research highlights: The results point to out the feasibility of applying ARA to ecological datasets as a tool for detecting ecological patterns of coexistence between species and the ecosystems functioning.Keywords: data mining; coexistence; semideciduous forests; deciduous forests; biotic interaction. 

scholarly journals Association Rules Analysis on FP-Growth Method in Predicting Sales

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan ◽  
Mesran Mesran ◽  
Andre Hasudungan Lubis ◽  
Ali Ikhwan ◽  
Supiyandi
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Frequent Itemset ◽  
Frequent Pattern ◽  
Data Set ◽  
Pattern Processing ◽  
Large Databases ◽  
Growth Method ◽  
Association Rules Analysis ◽  
A Company

Sales transaction data on a company will continue to increase day by day. Large amounts of data can be problematic for a company if it is not managed properly. Data mining is a field of science that unifies techniques from machine learning, pattern processing, statistics, databases, and visualization to handle the problem of retrieving information from large databases. The relationship sought in data mining can be a relationship between two or more in one dimension. The algorithm included in association rules in data mining is the Frequent Pattern Growth (FP-Growth) algorithm is one of the alternatives that can be used to determine the most frequent itemset in a data set.

scholarly journals Integrating Data Mining Techniques for Naïve Bayes Classification: Applications to Medical Datasets

Computation ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 99
Author(s):  
Pannapa Changpetch ◽  
Apasiri Pitpeng ◽  
Sasiprapa Hiriote ◽  
Chumpol Yuangyai
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Classification Accuracy ◽  
Naive Bayes ◽  
Classification Tree ◽  
Naïve Bayes ◽  
Naive Bayes Classifier ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
Association Rules Analysis

In this study, we designed a framework in which three techniques—classification tree, association rules analysis (ASA), and the naïve bayes classifier—were combined to improve the performance of the latter. A classification tree was used to discretize quantitative predictors into categories and ASA was used to generate interactions in a fully realized way, as discretized variables and interactions are key to improving the classification accuracy of the naïve Bayes classifier. We applied our methodology to three medical datasets to demonstrate the efficacy of the proposed method. The results showed that our methodology outperformed the existing techniques for all the illustrated datasets. Although our focus here was on medical datasets, our proposed methodology is equally applicable to datasets in many other areas.

A Comprehensive Evaluation System of Association Rules Based on AHP

2013 ◽  
Vol 427-429 ◽  
pp. 1907-1910
Author(s):  
Jing Bo Yuan ◽  
Xiao Lin Wei ◽  
Shun Li Ding
Keyword(s):  
Data Mining ◽  
Analytic Hierarchy Process ◽  
Association Rules ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Analytic Hierarchy ◽  
Comprehensive Evaluation System ◽  
Association Rules Analysis ◽  
Mining Algorithms ◽  
Hierarchy Process

Association rules analysis is an important subject in data mining. At present, association rules mining algorithms frequently generate a large number of association rules, but most of the algorithm evaluations make advances only from an aspect, which makes the users select difficultly. Therefore, the comprehensive evaluation of association rules has become highly necessary. A comprehensive evaluation system of association rules based on the AHP (Analytic Hierarchy Process) was presented, which can evaluate the association rules from multi-angle and multi-dimensional. Many evaluation results are integrated into the system, eventually presenting a unified comprehensive coefficient to users. Practical data make it clear that the comprehensive evaluation system is rational and superior.

scholarly journals Application of Association Rules Analysis in Mining Adverse Drug Reaction Signals

2021 ◽  
Vol 11 (22) ◽  
pp. 10828
Author(s):  
Jianxiang Wei ◽  
Jimin Dai ◽  
Yingya Zhao ◽  
Pu Han ◽  
Yunxia Zhu ◽  
...  
Keyword(s):  
Data Mining ◽  
Signal Detection ◽  
Association Rules ◽  
Public Health Problem ◽  
Detection Methods ◽  
Drug Risk ◽  
Spontaneous Reports ◽  
Optimal Thresholds ◽  
Data Source ◽  
Association Rules Analysis

Adverse drug reactions (ADRs) are increasingly becoming a serious public health problem. Spontaneous reporting systems (SRSs) are an important way for many countries to monitor ADRs produced in the clinical use of drugs, and they are the main data source for ADR signal detection. The traditional signal detection methods are based on disproportionality analysis (DPA) and lack the application of data mining technology. In this paper, we selected the spontaneous reports from 2011 to 2018 in Jiangsu Province of China as the research data and used association rules analysis (ARA) to mine signals. We defined some important metrics of the ARA according to the two-dimensional contingency table of ADRs, such as Confidence and Lift, and constructed performance evaluation indicators such as Precision, Recall, and F1 as objective standards. We used experimental methods based on data to objectively determine the optimal thresholds of the corresponding metrics, which, in the best case, are Confidence = 0.007 and Lift = 1. We obtained the average performance of the method through 10-fold cross-validation. The experimental results showed that F1 increased from 31.43% in the MHRA method to 40.38% in the ARA method; this was a significant improvement. To reduce drug risk and provide decision making for drug safety, more data mining methods need to be introduced and applied to ADR signal detection.

scholarly journals ON THE USE OF SHORTWAVE INFRARED FOR TREE SPECIES DISCRIMINATION IN TROPICAL SEMIDECIDUOUS FOREST

2015 ◽  
Vol XL-3/W3 ◽  
pp. 473-476 ◽  
Author(s):  
M. P. Ferreira ◽  
M. Zortea ◽  
D. C. Zanotta ◽  
J. B. Féret ◽  
Y. E. Shimabukuro ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Tree Species ◽  
Forest Restoration ◽  
Hyperspectral Data ◽  
Support Vector ◽  
Species Discrimination ◽  
Semideciduous Forest ◽  
Linear Discriminant ◽  
Average Accuracy ◽  
Shortwave Infrared

Tree species mapping in tropical forests provides valuable insights for forest managers. Keystone species can be located for collection of seeds for forest restoration, reducing fieldwork costs. However, mapping of tree species in tropical forests using remote sensing data is a challenge due to high floristic and spectral diversity. Little is known about the use of different spectral regions as most of studies performed so far used visible/near-infrared (390-1000 nm) features. In this paper we show the contribution of shortwave infrared (SWIR, 1045-2395 nm) for tree species discrimination in a tropical semideciduous forest. Using high-resolution hyperspectral data we also simulated WorldView-3 (WV-3) multispectral bands for classification purposes. Three machine learning methods were tested to discriminate species at the pixel-level: Linear Discriminant Analysis (LDA), Support Vector Machines with Linear (L-SVM) and Radial Basis Function (RBF-SVM) kernels, and Random Forest (RF). Experiments were performed using all and selected features from the VNIR individually and combined with SWIR. Feature selection was applied to evaluate the effects of dimensionality reduction and identify potential wavelengths that may optimize species discrimination. Using VNIR hyperspectral bands, RBF-SVM achieved the highest average accuracy (77.4%). Inclusion of the SWIR increased accuracy to 85% with LDA. The same pattern was also observed when WV-3 simulated channels were used to classify the species. The VNIR bands provided and accuracy of 64.2% for LDA, which was increased to 79.8 % using the new SWIR bands that are operationally available in this platform. Results show that incorporating SWIR bands increased significantly average accuracy for both the hyperspectral data and WorldView-3 simulated bands.

scholarly journals Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues for Human Participatory Based on Association Rules

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhi Li ◽  
Xuyu Li ◽  
Runhua Tang ◽  
Lin Zhang
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Total Sample ◽  
Web Pages ◽  
Apriori Algorithm ◽  
Cyber Crime ◽  
Cyber Attack ◽  
Security Issues ◽  
The Relationship ◽  
Cyberspace Security

This study explored the global cyberspace security issues, with the purpose of breaking the stereotype of people’s cognition of cyberspace problems, which reflects the relationship between interdependence and association. Based on the Apriori algorithm in association rules, a total of 181 strong rules were mined from 40 target websites and 56,096 web pages were associated with global cyberspace security. Moreover, this study analyzed support, confidence, promotion, leverage, and reliability to achieve comprehensive coverage of data. A total of 15,661 sites mentioned cyberspace security-related words from the total sample of 22,493 professional websites, accounting for 69.6%, while only 735 sites mentioned cyberspace security-related words from the total sample of 33,603 non-professional sites, accounting for 2%. Due to restrictions of language, the number of samples of target professional websites and non-target websites is limited. Meanwhile, the number of selections of strong rules is not satisfactory. Nowadays, the cores of global cyberspace security issues include internet sovereignty, cyberspace security, cyber attack, cyber crime, data leakage, and data protection.

How Useful Can Be Data Mining For A Continuos Speech Therapist’s Education?

2014 ◽  
Vol 1 (1) ◽  
pp. 339-342
Author(s):  
Mirela Danubianu ◽  
Dragos Mircea Danubianu
Keyword(s):  
Data Mining ◽  
Information And Communication Technology ◽  
Association Rules ◽  
Communication Technology ◽  
Speech Therapy ◽  
Proper Treatment ◽  
Speech Impairments ◽  
Information And Communication ◽  
Specific Education

AbstractSpeech therapy can be viewed as a business in logopaedic area that aims to offer services for correcting language. A proper treatment of speech impairments ensures improved efficiency of therapy, so, in order to do that, a therapist must continuously learn how to adjust its therapy methods to patient's characteristics. Using Information and Communication Technology in this area allowed collecting a lot of data regarding various aspects of treatment. These data can be used for a data mining process in order to find useful and usable patterns and models which help therapists to improve its specific education. Clustering, classification or association rules can provide unexpected information which help to complete therapist's knowledge and to adapt the therapy to patient's needs.

HUBUNGAN PERAN KADER POSYANDU DENGAN STATUS GIZI BALITA

2018 ◽  
Vol 9 (02) ◽  
pp. 192
Author(s):  
Wiwid Wahyuningsih ◽  
Atik Setiyaningsih
Keyword(s):  
Nutritional Status ◽  
Total Sample ◽  
Nutrition Status ◽  
P Value ◽  
Chi Square ◽  
Cross Sectional ◽  
Central Java ◽  
Good Nutrition ◽  
Nutritional Status Of Children

ABSTRAKLatar Belakang : Keberadaan kader di posyandu sebagai salah satu sistem penyelenggarakan pelayanan sangat dibutuhkan. Mereka adalah ujung tombak  pelayanan kesehatan yang merupakan kepanjangtanganan puskesmas Jawa Tengah tahun 2011 jumlah gizi kurang 5,35% dan gizi buruk 0,10%. Untuk Kabupaten Semarang dari 23.562 balita yang ditimbang pada tahun 2011 gizi lebih 1,13%, gizi baik 93,51%, gizi kurang 4,86% dan gizi buruk 0,49% (DepKes Prov Jateng, 2011). Tujuan Penelitian : Penelitian ini bertujuan untuk mengetahui hubungan peran kader posyandu dengan status gizi balita. Metode Penelitian : Desain penelitian ini adalah survey analitik dengan menggunakan pendekatan cross sectional. Populasi dalam penelitian ini adalah seluruh balita di Posyandu Mawar di Desa Gedangan sejumlah 40 responden, dengan teknik total sampling dan analisa data chi square. Hasil Penelitian : Hasil perhitungan chi square di peroleh X² hitung 10.644 pada df=4, P.value 0.031 dimana probabilitas lebih kecil dari level of significant 5 % (0,001 < 0,05) berarti Ha diterima dan Ho ditolak. Kesimpulan : ada hubungan antara peran kader posyandu dengan status gizi pada balita.Kata Kunci : peran kader , status gizi balitaCADERE ROLE RELATIONSHIP WITH NUTRITIONAL STATUS OF CHILDREN POSYANDUABSTRACTBackground : posyandu cadre in Existence as one of the 56th's service system is urgently needed. They are the tip of the Spear is a kepanjangtanganan health services clinics in Central Java in 2011 the amount of nutrition less 5.35% 0.10% and malnutrition. To Semarang from 23.562 toddler who weighed in 2011 more nutritional 1.13%, 93,51%, good nutrition nutrition less 4.86% and 0.49% poor nutrition (Department of Health Central Java Prov., 2011). Objective : the research aims to find out the relationship role of posyandu cadre with the nutritional status of children. Methods : the design of this research is a survey using the analytic approach of cross sectional. The population in this study are all the toddlers at the Rose in the village of Posyandu Gedangan some 38 respondents, with total sample techniques and data analysis a chi square. The results :. The chi square calculation results in getting X ² count 10.644 on df = 4, P. value 0.031 where probability is smaller than the level of significant 5% (0.001 < 0.05) mean Ha Ho accepted and rejected. Conclusion : there is a connection between the role of cadres of posyandu with nutritional status on toddlers.Keywords : the role of cadres, toddler nutrition status

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