Machine learning plays a vital role in health care industry. It is very important in Computer Aided Diagnosis. Computer Aided Diagnosis is a quickly developing dynamic region of research in medicinal industry. The current specialists in machine learning guarantee the enhanced precision of discernment and analysis of diseases. The computers are empowered to think by creating knowledge by learning. This procedure enables the computers to self-learn individually without being explicitly programed by the programmer .There are numerous sorts of Machine Learning Techniques and which are utilized to classify the data sets. They are Supervised, Unsupervised and Semi-Supervised, Reinforcement, deep learning algorithms. The principle point of this paper is to give comparative analysis of supervised learning algorithms in medicinal area and few of the techniques utilized as a part of liver disease prediction.
Application of ANN to the electricity price forecasting is gaining importance in the context of electricity markets. This paper presents four different ANN models used for forecasting the electricity price. They are the classical back propagation neural network model, radial basis function neural network model, genetic algorithm based neural network and a direct non-iterative state estimation based neural network model. A case study is made with the downloaded data of the day-ahead pool market prices of the Iberian Energy Derivatives Exchange using the above four different ANN models and the results are compared.
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