International Journals
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Item NONCOMMUNICABLE DISEASES IN INDIA AND CHINA(Journal of The Gujarat Research Society, 2019-12) M, Rajeswari; S, SuhitaThe non communicable diseases are becoming a major threat to world. The continuous monitoring of non communicable diseases helps us to take precautions against them. The paper is based on non communicable diseases affecting the different age group. Non communicable diseases is not transferred from one person to other person directly. Non communicable diseases may be chronic or acute. In 2012, NCD’s caused 68% of all deaths (38 million) up from 60% in 2000.Item CONSUMER BEHAVIOUR(Journal of The Gujarat Research Society, 2019-12) M, Rajeswari; M, SowndaryaThis analysis is based upon the consumers’ buying behavior. The common factor of consumers’ buying behavior is price. The rise in price leads to less purchase of the products. This paper aims at identifying the product that is sold least in order to make the store order the same in less quantity so that loss due to stock of expired products could be avoided. This paper also aims at identifying the products that are most essential to the consumers which may be purchased by the consumers irrespective of the rise in price so the profit of the store could be increased.Item TEMPERATURE AND TIME SERIES ANALYSIS USING CLUSTERING AND SIMPLE K-MEANS(Journal of The Gujarat Research Society, 2019-12) M, Rajeswari; T A, Maria AntonetteClustering is a type of learning technique in which a set of objects are grouped together in such a way that each group of cluster has similar characteristics in them. It is much utilizes in exploratory data mining. In other words clusters are the aggregation of similar objects which share common characteristics the types of clustering methods, such as connectivity, centroid , distribution and density based clustering. Here we are going to see temperature of sao paulo. To analyse this we are going to use clustering method in the r programming language. The method of clustering is used in many fields like the pattern recognition, image analysis, data compression, information retrieval, bio informatics etc.Item ANALYSIS OF STUDENTS' PERFORMANCE BASED ON FACTORS USING FAMILY SIZE AND TRAVEL TIME(Journal of The Gujarat Research Society, 2019-12) M, Rajeswari; B, DharaniyaThe student performance of the students performance of the different issues that affects the student with the causes of cluster creation with the cause of cluster creation with the help of cluster creation with the help of k means key in that family issues the studies of students changes the students distraction in their way of achievement in the similar way of getting the students performance using the cluster in the data object of given attributes with an cluster form mid-point or which are termed to me cluster and the centroid value of data to be calculated by k-means to identify the affect of family issues in student day today objectives.Item FOIL BASED FEATURE SUBSET SELECTION ALGORITHM FOR PREDICTING INFERTILITY ON IVF USING CLUSTERING(Speak Foundation-International Journal of Management and Social Sciences(IJMSS), 2018-12) S, Deepika; M, RajeswariThis paper illustrates the concept of clustering and classification technique to identify important criteria for the infertility couples to find the success rate of In-vitro Fertilization treatment. A FOIL algorithm, First creates the construction of minimum spanning tree after that the partition the data into each tree by clustering the similar features. Selected features are represented into clusters. At last feature interaction is done by combining the features appeared in the previous circumstances of all FOIL rules, which will achieve a candidate feature subset to avoid redundant features and reserves interactive ones. Thus, the proposed paper will determine the accuracy and efficiency of IVF treatment using R programming.Item PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM(Speak Foundation-International Journal of Management and Social Sciences(IJMSS), 2018-12) M, Rajeswari; S, DeepikaCompetitive advantage is gained by firm through new areas such as data warehousing, data mining and campaign management software have made Customer Relationship Management(CRM). This research aims to develop methodologies for predicting customer churn in advance, while keeping misclassification rates to a minimum.Item INFERTILITY PREDICTIVE ANALYSIS ON IVF BASAED ON SIGNIFICANT FEATURE SELECTION USING DATA MINING TECHNIQUES(Speak Foundation-International Journal of Management and Social Sciences(IJMSS), 2018-12) S, Deepika; M, RajeswariThis paper elucidates the process by applying clustering and classification technique to spot major procedures for the infertility couples to decide the success rate of In-vitro Fertilization treatment. There are factors which lead to infertility like age, education, economical backlog, Body Mass Index(BMI) and obesity which causes changes in hormonal levels and heredity etc., for infertility couples. The constraints with high sway factor can be well-known by apply the proper decrease/unrelated algorithm, which destroy the parameters that has a less important role in determining the success rate of particular patients. Data mining plays vital role in its pre-processing techniques to increase prediction accuracy and find which treatment will be perfect for the patient. A FAST-FOIL algorithm, First became the construction of minimum spanning tree, after that the partition the data into each tree by clustering the similar features. Selected features are represented into clusters. Thus, the proposed paper will determine the accuracy of IVF treatment compared with ZIFT and GIFT using MATLAB.Item DEVELOPMENT OF MODIFIED RIPPER ALGORITHM TO PREDICT CUSTOMER CHURN(International Journal of Advance Research in Engineering Science and Technology, 2018-02) M, RajeswariTechnologies such as data warehousing, data mining, and campaign management software have made Customer Relationship Management (CRM) a new area where firms can gain a competitive advantage. Particularly through data mining a process of extracting hidden predictive information from large databases, organizations can identify their valuable customers, predict future behaviors, and enable firms to make proactive, knowledge-driven decisions. Data Mining along with Customer Relationship Management plays a vital role in today’s business environment. Customer churn, a process of retaining customer is a major issue. Prevention of customer churn is a major problem because acquiring new customer is more expensive than holding existing customers. In order to prevent churn several data mining techniques have been proposed. One among such method is solving class imbalance which has not received much attention in the context of data mining. This paper describes Customer Relationship Management (CRM), customer churn and class imbalance and proposes a methodology for preventing customer churn through class imbalance.Item DESIGN OF MODIFIED RIPPER ALGORITHM TO PREDICT CUSTOMER CHURN(SPC(Science Publishing Corporation), International Journal of Engineering and Technology, 2015) M, Rajeswari; T, DeviTechnologies such as data warehousing, data mining, and campaign management software have made Customer Relationship Management (CRM) a new area where firms can gain a competitive advantage. It is becoming common knowledge in business that retaining existing customers is an important strategy to survive in industry. Once identified, these customers can be targeted with proactive retention campaigns in a bid to retain them. These proactive marketing campaigns usually involve the offering of incentives to attract the customer into carrying on their service with the supplier. These incentives can be costly, so offering them to customers who have no intention to defect results in lost revenue. Also many predictive techniques do not provide significant time to make customer contact. This time restriction does not allow sufficient time for capturing those customers who are intending to leave. This research aims to develop methodologies for predicting customer churn in advance, while keeping misclassification rates to a minimum.