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Machine learning algorithm are used to produce new pattern from compound data set. To cluster the patient heart condition to check whether his /her heart normal or stressed or highly stressed k-means clustering algorithm is applied on the patient dataset. From the results of clustering ,it is hard to elucidate and to obtain the required conclusion from these clusters. Hence another algorithm, the decision tree, is used for the exposition of the clusters of . In this work, integration of decision tree with the help of k-means algorithm is aimed. Another learning technique such as SVM and Logistics regression is used. Heart disease prediction results from SVM and Logistics regression were compared.

In wireless sensing element networks (WSNs),sensing element nodes or operated by little batteries, therefore they need restricted energy resources which require careful utilization. The planned algorithmic rule is associate degree vitality economical so as to handle trade –off between packet delay and transmission power, and delay economical we have a tendency to develop 3 ANTLION schemes supported power-delay limitations of the heterogeneous WSN. We have a tendency to devise a theoretical framework to figure the common delay and stability region for every planned theme and compare the performance of ANTLION and traditional Clustering. A new hybrid routing protocol is proposed by incorporating the routing concept of adhoc network into the hierarchical clustering routing protocol LEACH of the wireless sensor networks namely Quadrant Based LEACH (ANTLION)..

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