Efficient Decision Tree using Machine Learning Tools for Acute Ailments

Machine learning is a part of data mining which learns from previously fed data. It is one of the best tools to classify and cluster the data. These homemade medicines are used in villages to treat diseases. Thus, using the combined knowledge of Ayurveda and machine learning, the data can be used to find the target value. This target value can be modified for personal use, benefit and treatment according to the disease. In this paper, we have used machine learning algorithms and classified the data to check widely used Ayurvedic medicines. We used tools like Scikit learn and Jupiter notebook to plan a Decision tree. This is mainly used for algorithm solving and data prediction. The basic assumption of machine learning is to construct algorithms that can take input data. This input data is statistically analyzed to predict output. As we know that the current scenario of predicting earthquakes can be done by the next artificial intelligence frontier. Thus, advancements in machine learning and artificial intelligence today will have an immense change in future.