IntroductionThe occlusal relationship of primary dentition plays a vital role in predicting malocclusion in permanent dentition because primary dentition is the stepping stone for permanent dentition.AimThe aim of the study was to assess the occlusal relationships between the primary canine and the primary molar in the primary dentition in centric occlusion and also spacing in primary dentition among a group of 3- to 6-year-old children.Materials and methodsThe survey was based on examination of the primary dentition of 100 school children aged 3–6 years from Chennai, Tamil Nadu, India. The examination was done using pen light and mouth mirror. The occlusal assessment was done only on children who are healthy and free from extensive caries. The primary molar relationship and the canine relationship were assessed using Foster and Hamilton criteria with the teeth in centric occlusion.ResultsThe study showed that, out of 100 school children, the molar relationship 56% had mesial step followed by 36% with flush terminal relationship and 8% with distal step relationship and out of 100 children, the canine relationship 61% of children had class III relationship followed by 27% class I relationship and 12% class II relationship. And around 54% had spacing out of which, maximum spacing was found only in the upper anteriors.ConclusionThe survey concluded showing that the mesial step primary relationship was more common among 5- to 6-year-old children followed by flush terminal relationship and distal step relationship. The class III primary canine relationship was more common followed by classes I and II. Spacing was found more common in upper anteriors.How to cite this articleKumar D, Gurunathan D. Primary Canine and Molar Relationships in Centric Occlusion in 3 to 6-year-old Children: A Cross-sectional Survey. Int J Clin Pediatr Dent 2019;12(3):201–204.

The major objective of this study is to find accuracy in movie suggestion systems using machine learning algorithms namely Empirical Risk Minimisation Algorithm and Decision Tree Algorithm. Empirical Risk Minimisation algorithm and Decision Tree algorithm with sample size N = 10 was iterated 20 times for finding accuracy in movie suggestion systems.The Empirical riskminimisation algorithm produces a better accuracy of [92.02%] than the Decision tree algorithm [80.58%]. The significance of Empirical risk minimisation[p<0.05] for independent sample T-test is high.The comparison of results showed that the Empirical risk minimisation algorithm is significantly better for finding accuracy in movie suggestion systems when compared to the Decision tree algorithm