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ISSN 2063-5346
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A NOVEL APPROACH FOR PREDICTING HOUSE PRICE USING K-NEAREST NEIGHBOR ALGORITHM COMPARING ACCURACY PREDICTION WITH ARTIFICIAL NEURAL NETWORK

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Z.Sri Sai Swetha, R. Dhanalakshmi
» doi: 10.31838/ecb/2023.12.sa1.431

Abstract

Aim: This work is a comparative study of artificial intelligence Novel K-Nearest Neighbors Algorithm (KNN) and Novel Artificial neural network for the house price prediction system to improve the accuracy of house price prediction. Materials and methods: From Machine Learning, Novel K-Nearest Neighbors (N=10) and Novel Artificial neural network (N=10)methods are simulated by varying the KNN parameter and Novel Artificial neural network to optimize the pH.The sample size was calculated using the G power of 80% for two groups and there are 40 samples used in this work. Results: Based on the obtained results KNN has significantly better classification accuracy (67.92) compared to the Novel Artificial neural network algorithm (61.94) Statistical significance difference between long short term memory and Novel Artificial neural network was found to be 0.156 (p>0.05) which infers that both groups are insignificant. Conclusion:The ANN algorithm produces better results in prediction on house price monitoring to improve the price prediction accuracy than the Novel Artificial neural network algorithm.

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