Improving Classification in Data mining using Hybrid algorithm

Data mining is a powerful concept with great potential to predict future trends and behavior. It refers to the extraction of hidden knowledge from large datasets using techniques like statistical analysis, machine learning, clustering, neural networks and genetic algorithms. Hybrid algorithms for data mining are a logical combination of multiple pre-existing techniques to enhance performance and provide better results[11]. The hybrid algorithm proposed in this paper uses the concept of clustering and decision tree induction to classify the data samples. When the proposed approach is tested on real life datasets, the results obtained show improved accuracy in most cases.