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Application of Data Mining Techniques in Weather Prediction and Climate Change Studies Abstract-Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall,…
Data Mining for Patient Friendly Apnea Detection Abstract-Obstructive Sleep Apnea (OSA) is a common, but severely under-diagnosed sleep disorder that affects the natural breathing cycle during sleep with periods of reduced respiration or no airflow at all. It is our long-term goal to increase the percentage of diagnosed OSA cases and reduce the time to…
Data Mining for Patient Friendly Apnea Detection Abstract-Obstructive Sleep Apnea (OSA) is a common, but severely under-diagnosed sleep disorder that affects the natural breathing cycle during sleep with periods of reduced respiration or no air?ow at all. It is our long-term goal to increase the percentage of diagnosed OSA cases and reduce the time to…
Prediction of Heart Disease Using Machine Learning Algorithms Abstract-Heart disease is the one of the most common disease. This disease is quite common now a days we used different attributes which can relate to this heart diseases well to find the better method to predict and we also used algorithms for prediction. Naive Bayes, algorithm…
Prediction of Rainfall using Datamining technique over Assam Abstract-Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. Weather is one of the meteorological data that is rich in important knowledge. The most important climatic…
Stocks Market Prediction Using Support Vector Machine Abstract-A lot of studies provide strong evidence that traditional predictive regression models face significant challenges in out-of sample predictability tests due to model uncertainty and parameter instability. Recent studies introduce particular strategies that overcome these problems. Support Vector Machine (SVM) is a relatively new learning algorithm that has…
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